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<p>在这一页上</p> <span class="sc-fQejPQ fTFtno grey" property="background-color" color="#D8D8D8"><a class="sc-htpNat bUhGXt link sc-fZwumE cLQMJq" href="#abstract" aria-label="">文摘</a></span> <span class="sc-fQejPQ fTFtno grey" property="background-color" color="#D8D8D8"><a class="sc-htpNat bUhGXt link sc-fZwumE cLQMJq" href="#introduction" aria-label="">介绍</a></span> <span class="sc-fQejPQ fTFtno grey" property="background-color" color="#D8D8D8"><a class="sc-htpNat bUhGXt link sc-fZwumE cLQMJq" href="#preliminaries" aria-label="">预赛</a></span> <span class="sc-fQejPQ fTFtno grey" property="background-color" color="#D8D8D8"><a class="sc-htpNat bUhGXt link sc-fZwumE cLQMJq" href="#related-work" aria-label="">相关工作</a></span> <span class="sc-fQejPQ fTFtno grey" property="background-color" color="#D8D8D8"><a class="sc-htpNat bUhGXt link sc-fZwumE cLQMJq" href="#evaluation" aria-label="">评价</a></span> <span class="sc-fQejPQ fTFtno grey" property="background-color" color="#D8D8D8"><a class="sc-htpNat bUhGXt link sc-fZwumE cLQMJq" href="#discussion" aria-label="">讨论</a></span> <span class="sc-fQejPQ fTFtno grey" property="background-color" color="#D8D8D8"><a class="sc-htpNat bUhGXt link sc-fZwumE cLQMJq" href="#conclusion" aria-label="">结论</a></span> <span class="sc-fQejPQ fTFtno grey" property="background-color" color="#D8D8D8"><a class="sc-htpNat bUhGXt link sc-fZwumE cLQMJq" href="#data-availability" aria-label="">数据可用性</a></span> <span class="sc-fQejPQ fTFtno grey" property="background-color" color="#D8D8D8"><a class="sc-htpNat bUhGXt link sc-fZwumE cLQMJq" href="#conflicts-of-interest" aria-label="">的利益冲突</a></span> <span class="sc-fQejPQ fTFtno grey" property="background-color" color="#D8D8D8"><a class="sc-htpNat bUhGXt link sc-fZwumE cLQMJq" href="#acknowledgments" aria-label="">确认</a></span> <span class="sc-fQejPQ fTFtno grey" property="background-color" color="#D8D8D8"><a class="sc-htpNat bUhGXt link sc-fZwumE cLQMJq" href="#references" aria-label="">引用</a></span> <span class="sc-fQejPQ fTFtno grey" property="background-color" color="#D8D8D8"><a class="sc-htpNat bUhGXt link sc-fZwumE cLQMJq" href="#copyright" aria-label="">版权</a></span> </div> </div> </div> <div class="threeColumn__ContentWrapper-sc-1bf4078-3 bbzREB contentWrapper"> <div class="threeColumn__Content-sc-1bf4078-4 jknsZc content"> <div class="articleContent__ArticleContentsWrapper-sc-2yl9jy-0 eSvjPB article_contents"> <div class="articleContent__ArticleContentsSectionsWrapper-sc-2yl9jy-1 jntdRu article_contents__sections_wrapper"> <div class="articleContent__ArticleWrapper-sc-2yl9jy-2 hAzjHP"> <div class="sc-cqCuEk dDomlX article_header_class"> <p class="sc-ipZHIp hDKZCZ article_type">研究文章|开放获取</p> <div class="sc-iGrrsa eZlme article_citation"> 体积 2020年 <span class="sc-dEoRIm gusDuS">|</span>文章的ID 8630748 <span class="sc-dEoRIm gusDuS">|</span> 19 页面 <span class="sc-dEoRIm gusDuS">|</span> <a class="sc-htpNat bUhGXt link sc-jtggT iUDBGe" href="https://doi.org/10.1155/2020/8630748" aria-label="Doi-link">https://doi.org/10.1155/2020/8630748</a> </div> <h1 class="sc-jAaTju cxkaTM sc-bmyXtO lmNMHJ article_title">设备内置检测重新包装Android恶意软件通过交通集群</h1> </div> <div class="sc-jeCdPy bpzNtR article_authors"> <hr class="sc-likbZx PHYWq hr__author"> <span class="">高峰,他,<sup>1,2</sup></span> <span class="">Bingfeng徐,<sup>3</sup></span> <span class="">张陆,<sup>4</sup> 和</span> <span class=""><b>海特朱</b><a class="sc-htpNat bUhGXt link" href="mailto:" aria-label="Mail to Author Option"><img alt="" class="sc-EHOje cPuqxU sc-jtRlXQ jIaDFG" title="" role="presentation" 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height="16"></a><a class="sc-htpNat bUhGXt link" href="https://orcid.org/0000-0002-5840-2251" aria-label="Redirect to Doi" target="_blank"><img alt="" class="sc-EHOje cPuqxU sc-bGbJRg flqdYJ" title="" role="presentation" src="data:image/svg+xml;base64,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" height="16"></a><sup>1</sup></span> <div class="sc-ePZHVD eecoTM isHide"> <p><sup>1</sup><span>物联网学院,南京邮电大学,南京210003年,中国</span></p> <p><sup>2</sup><span>重点实验室的计算机网络和信息集成(东南大学),教育部,南京,中国</span></p> <p><sup>3</sup><span>南京林业大学信息科学技术学院,南京210037年,中国</span></p> <p><sup>4</sup><span>信息工程学院、南京大学金融与经济,210046年南京,中国</span></p> </div> <button class="sc-kEYyzF gRIXYh sc-bEjcJn cFrLKZ" color="">显示更多</button> </div> <div class="articleContent__EditorWrapper-sc-2yl9jy-3 evMkvU"> <div class="articleContent__TextWrapper-sc-2yl9jy-8 fYrLtk"> <b>学术编辑器:</b>皮诺Caballero-Gil</d我v> <div class="articleContent__PublicationTimeLineWrapper-sc-2yl9jy-4 fjviok"> <div class="articleContent__PublcationCol-sc-2yl9jy-5 hgKieC notPublished"> <span class="articleContent__PublicationField-sc-2yl9jy-6 cIribm">收到了</span> <span class="articleContent__PublicationValue-sc-2yl9jy-7 khHUcu">2019年7月3日</span> </div> <div class="articleContent__PublcationCol-sc-2yl9jy-5 hgKieC notPublished"> <span class="articleContent__PublicationField-sc-2yl9jy-6 cIribm">修改后的</span> <span class="articleContent__PublicationValue-sc-2yl9jy-7 khHUcu">2020年3月14日</span> </div> <div class="articleContent__PublcationCol-sc-2yl9jy-5 hgKieC notPublished"> <span class="articleContent__PublicationField-sc-2yl9jy-6 cIribm">接受</span> <span class="articleContent__PublicationValue-sc-2yl9jy-7 khHUcu">2020年5月18日</span> </div> <div class="articleContent__PublcationCol-sc-2yl9jy-5 hgKieC isPublished"> <span class="articleContent__PublicationField-sc-2yl9jy-6 cIribm">发表</span> <span class="articleContent__PublicationValue-sc-2yl9jy-7 khHUcu">2020年5月31日</span> </div> </div> </div> <article class="sc-kZmsYB iukjRu article_body "> <div> <div class="xml-content"> <h4 class="header" id="abstract">文摘</h4> <p>恶意软件已经成为在Android平台上的一个重要问题。为了抵御Android恶意软件,研究人员提出了几种设备内置检测方法。通常,这些设备上检测方法由两个步骤:(i)提取从移动设备和应用程序的行为特征(2)向远程服务器提取的特征(如云平台)进行分析。通过监控行为的应用程序运行在移动设备上,可用的方法可以检测可疑应用程序(简单,<我>应用程序</我>准确)。然而,移动设备通常是资源有限。特征提取和大规模数据传输会消耗大量的电力和CPU资源;因此,移动设备的性能会退化。为了解决这个问题,我们提出一种新颖的方法来检测Android恶意软件通过集群应用程序的流量计算节点。首先,一个新的集成架构的云,边缘,和移动设备为Android恶意软件检测。重新包装Android恶意软件,网络流量内容和统计数据与检测特征提取的边缘。最后,在云计算中,应用相似性计算,相似度值自动聚集到单独的原始应用程序和恶意软件。实验结果表明,该方法可以检测重新包装Android恶意软件精度高和对移动设备的性能影响最小。</p> <span class="end-abs"></span> <h4 id="introduction">1。介绍</h4> <p>最近,Android平台(smartwatch,如智能手机和平板电脑)已成为越来越受欢迎的世界。根据Statista, Android是占全球手机操作系统市场74%以上的截至2019年12月(<a href="#B1">1</a>]。Android操作系统受欢迎的最重要的一个原因是,移动用户可以方便地从应用程序商店下载各种类型的应用程序(<a href="#B2">2</a>]。例如,一个官方的安卓市场,即谷歌商店,2020年1月已经有超过290万个应用程序(<a href="#B3">3</a>]。这些功能丰富的应用程序使Android平台有吸引力和充满活力。</p> <p>Android应用程序。,Android Package Kit (APK) files, are archives in ZIP format, which include developer bytecodes, resource files, and a manifest file. Unfortunately, in contrast to traditional executable software, Android apps are easy to repackage. With open-source tools such as apktool (<a href="https://github.com/iBotPeaches/Apktool" target="_blank">https://github.com/iBotPeaches/Apktool</a>)和jadx (<a href="https://github.com/skylot/jadx" target="_blank">https://github.com/skylot/jadx</a>),可以很容易地添加代码或修改资源文件来实现不同的目标。例如,恶意软件作者可以贪污广告代码在流行的应用程序来赚钱或贪污恶意代码窃取用户隐私信息(例如,Xavir恶意软件感染超过800 android应用程序。这些重新打包应用程序通常是自签名的,不需要的移动设备)。根据(<a href="#B4">4</a>- - - - - -<a href="#B6">6</a>),大多数Android恶意软件程序重新打包应用程序,大多数新Android恶意软件样本多态变量已知的恶意软件。重新包装Android恶意软件Android安全正在成为一个实质性的威胁。</p> <p>研究人员广泛调查(重新包装)Android恶意软件的检测,并提出了几种方法和评估(<a href="#B7">7</a>- - - - - -<a href="#B14">14</a>]。以前一般可以分为工作<我>脱机</我>和<我>设备内置</我>检测。脱机检测通常采用安全分析程序分析的APK文件专用分析服务器。分析程序可以检查的apk签名或动态运行它们在真实或虚拟执行环境来记录他们的行为(<a href="#B15">15</a>]。如果发现恶意代码或行为,应用程序将被判断为恶意软件。脱机检测也可以通过网络监控(<a href="#B14">14</a>]。我们将参考脱机这种类型的检测方法<我>基于网络的方法</我>在下面。</p> <p>在本地设备上检测是实现部分或全部,也就是说,在用户的移动设备。识别恶意软件的安装程序是未遂。技术上、设备上检测也识别恶意软件通过分析应用程序的行为。相比脱机检测、设备内置检测可以检测恶意软件运行在移动用户的设备和识别更复杂的恶意程序,例如那些由指定触发事件。例如,通过观察应用网络行为的偏差在移动设备,可以检测自更新恶意软件可能会触发指定的地理位置,设备类型、操作系统版本(<a href="#B8">8</a>]。然而,设备内置检测更具挑战性由于资源有限的移动设备。</p> <p>通常,几个步骤应该进行检测恶意Android应用程序在移动设备。首先,检测特性,比如用户的操作行为,API用法和应用网络行为应该定义和提取。然后,根据提取的特征,检测模型构造,,最后,新的应用与恶意软件检测的构造模型。根据这些步骤执行,当前的方法可以分成两个主要团体:<我>客户端</我>检测和<我>服务器端</我>检测(<a href="#B14">14</a>]。客户端检测,这些步骤都是在移动设备上进行的,而对于服务器端检测,主要步骤(模型建设和恶意软件检测)在远程服务器上进行。</p> <p>在实践中,应用程序客户端方法可以限制,因为他们消耗大量的资源和权力。根据文献[<a href="#B8">8</a>),10 Android恶意软件检测模型的存储需要7272 kB<svg height="7.35473pt" id="M1" style="vertical-align:-0.3499303pt" version="1.1" viewbox="-0.0498162 -7.0048 7.75925 7.35473" width="7.75925pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <path d="M535 290V340H323V533H265V340H52V290H265V84H323V290H535ZM535 -22V28H52V-22H535Z" id="g117-37"></path> </g> </svg>15内存消耗,这些模型的学习需要13%<svg height="7.35473pt" id="M2" style="vertical-align:-0.3499303pt" version="1.1" viewbox="-0.0498162 -7.0048 7.75925 7.35473" width="7.75925pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g117-37"></use> </g> </svg>1.5 CPU消耗。更糟糕的是,模型训练和保存越多,消耗更多的资源和权力。因此,服务器端方法通常采用(<a href="#B16">16</a>]。然而,服务器端方法的资源和电力消耗居高不下(例如,7%的性能开销和电池大约3%的开销<a href="#B17">17</a>])。这是因为检测功能仍在移动设备(主要是收集和处理<a href="#B10">10</a>,<a href="#B17">17</a>]。</p> <p>在本文中,我们提出一个新颖的方法检测重新包装Android恶意软件基于集群计算平台应用的交通优势。尽管Android恶意软件可以使用模拟器/沙箱检测[<a href="#B18">18</a>和包装<a href="#B19">19</a>,<a href="#B20">20.</a>阻碍了动态和静态分析,很难隐藏流量进行检查。我们的方法的基本策略是特征提取和预处理可以卸载到边缘。因此,移动设备的负载降低。Android恶意软件检测的设计架构包含三个组件:移动设备,边缘服务器,云。通常使用的移动设备,和一个额外的<我>edge-client</我>应用程序将被安装和运行在后台。edge-client应用运行相同的Android VPN应用等<我>数据包捕获</我>(<a href="https://play.google.com/store/apps/details?id=app.greyshirts.sslcapture&hl=enUS" target="_blank">https://play.google.com/store/apps/details?id=app.greyshirts.sslcapture&hl=enUS</a>),除了它只记录流的元,如流起始时间和流量的协议,它不需要保存和操作包内容。因此,它是轻量级的,将微不足道的负担强加给移动设备。</p> <p>边缘服务器收集的移动网络流量和提取检测特征的交通。交通边缘服务器进行的预处理,不仅可以减少发送的数据量也保护移动用户的隐私,因为云只能观察到粗粒度特性。提取的网络流量特性是发送到云进行最终处理。在云中,应用相似性计算基于接收到的特性。这些相似性值后自动聚集到单独的原始应用程序和重新包装的恶意软件。我们进行了大量的实验,结果表明,平均检测精度为96.9%。</p> <p>我们的主要贡献如下:<span class="list"><span class="list-item"><span class="list-label">(我)</span><span class="list-content">一个轻量级的、高效的框架,该框架是基于边缘检测的计算提出了Android恶意软件。典型的服务器端方法相比,该框架将对性能的影响最小的移动设备。此外,基于网络的方法相比,可以提高检测精度,可以更好的保护手机用户的隐私。</span></span><span class="list-item"><span class="list-label">(2)</span><span class="list-content">交通聚类方法的识别提出了重新包装Android恶意软件。我们集群的网络流量是由相同的应用程序来决定哪一个已经重新包装。首先,我们使用明文内容和流量统计特性计算程序之间的相似之处。然后,相似度值集群分离原始应用程序和自动重新包装的恶意软件。通过聚类,它是不必要的模型应用的网络行为或提前提取匹配签名恶意软件检测。因此,这种方法将会在实践中更有效。</span></span><span class="list-item"><span class="list-label">(3)</span><span class="list-content">广泛的公共数据集进行实验。</span></span></span></p> <p>本文的其余部分组织如下。Android恶意软件的预赛,边缘计算介绍了部分<a href="#sec2">2</a>。节<a href="#sec3">3</a>,我们将讨论相关的相关工作。部分<a href="#sec4">4</a>描述了新集成架构的云,边缘,为Android恶意软件检测和移动设备。方法提出了部分<a href="#sec5">5</a>。的实验评价方法的准确性和性能提出了部分<a href="#sec6">6</a>。我们讨论该方法的局限性<a href="#sec7">7</a>。最后,在节<a href="#sec8">8</a>,我们提出本文的结论和讨论潜在的未来的工作。</p> <h4 id="preliminaries">2。预赛</h4> <p>在本节中,我们介绍了关于Android恶意软件和边缘计算重要的概念,这是这项工作的基础。</p> <h5 id="sec2.1">2.1。Android恶意软件</h5> <p>作为讨论的部分<a href="#sec1">1</a>Android应用程序(上年)很容易重新包装,这是攻击者想方便创建Android恶意软件。事实上,大多数Android恶意软件是由重新包装产生良性的应用,特别是最喜欢的应用程序,以确保广泛扩散的恶意代码<a href="#B4">4</a>]。作为证据,MalGenome [<a href="#B21">21</a>),这是一个参考的数据集在Android安全社区,80%的恶意样本建立了通过重新包装其他应用程序。重新打包应用程序可以通过第三方市场分布,通常不需要筛选或完整性评估上传应用程序(<a href="#B22">22</a>]。例如,许多应用程序的F-Droid发现由同一个开发者(重新包装<a href="#B23">23</a>]。因此,在这项研究中我们主要检测恶意将Android应用程序重新打包。</p> <p>重新包装可以有效地检测到Android恶意软件分析其网络流量(<a href="#B7">7</a>,<a href="#B14">14</a>]。这是因为重新打包应用程序通常是功能化与远程服务器进行交互接收命令或返回敏感数据,和他们的网络行为将不同于原来的网络行为。为了更好的解释这个,我们反编译两个应用程序,即00575 de650f78413c91e8e613adf9099812f325aa9cf36c72e81c79b230f58f4 A55EA5807203CE31470D1905ED30F9267AE3459809DDA25C4F339197DE6486FE,比较相应的文件夹来识别新添加的文件。添加文件进一步分析(通过阅读Java代码)来调查他们的网络行为。在本例中,应用程序的名称是SHA256 APK文件的价值,和00575∗对应于原始应用程序和A55EA∗重新打包应用程序,我们使用<我>Jadx来</我>反编译的apk文件进行比较<我>WinMerge</我>(<a href="http://winmerge.org/" target="_blank">http://winmerge.org/</a>)。图<a href="//www.newsama.com/journals/scn/2020/8630748/fig1/" target="_blank">1</a>给出了比较结果。</p> <div class="floats-partial-section partial-carousel-wrapper" data-section="fig1"> <div class="floats-partial-content fig-content-fig1"> <div class="partial-carousel--single-image"> <img alt="" name="8630748.fig.001" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.001.svgz"> <br> <strong></strong> </div> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">图1</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/fig1/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 文件夹和文件,只存在于A55EA重新包装应用<sup>∗</sup>所表示的<我>只剩下</我>在第三列。</d我v> </div> </div> <p>如图<a href="//www.newsama.com/journals/scn/2020/8630748/fig1/" target="_blank">1</a>,总共有250额外的Java代码文件,而这些代码文件分布在来源/ com文件夹。我们仔细阅读这些添加Java代码并确定Android API<我>HttpPost</我>8倍和调用吗<我>HttpGet</我>调用5次。因此,至少有13流动不会产生的原始应用程序,即00575<sup>∗</sup>。因此,最初的应用可以有效地区别重新打包版本通过比较他们的网络流量。受这些观察结果,我们提出集群移动应用的交通分离原始应用程序和自动重新包装的恶意软件。</p> <h5 id="sec2.2">2.2。边缘计算</h5> <p>边缘计算可以定义的技术使计算被执行在网络的边缘,对下游数据代表云服务和上游数据代表物联网(物联网)服务(<a href="#B24">24</a>]。也许最重要的概念计算边缘的边缘可以包含任何计算和网络资源之间沿着路径移动/物联网设备和云数据中心。例如,边缘可能是一个电话一个聪明的手镯和云之间或智能电视和云计算之间的无线路由器,如果电话或无线路由器执行代表智能设备和云计算。在这些例子中,计算可能是隐私保护的数据匿名化或内容缓存的性能改进。图<a href="//www.newsama.com/journals/scn/2020/8630748/fig2/" target="_blank">2</a>说明了边缘的模式计算。</p> <div class="floats-partial-section partial-carousel-wrapper" data-section="fig2"> <div class="floats-partial-content fig-content-fig2"> <div class="partial-carousel--single-image"> <img alt="" name="8630748.fig.002" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.002.svgz"> <br> <strong></strong> </div> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">图2</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/fig2/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 边缘的计算模式。</d我v> </div> </div> <p>如图<a href="//www.newsama.com/journals/scn/2020/8630748/fig2/" target="_blank">2</a>,云计算功能,即。,edge servers are deployed at the edge of the network for data (pre) processing and forwarding. In edge computing, the mobile/IoT devices could send computation tasks to the edge servers, namely, the devices can distribute code to the edge to be executed; hence, the mobile/IoT devices can be designed to conduct complicated operations, such as machine learning or encryption. Similarly, the cloud may push services to the edge servers, and the edge can be deployed and updated online. In most cases, the devices should be connected to the edge and the cloud simultaneously, as represented by the solid and dotted lines in Figure<a href="//www.newsama.com/journals/scn/2020/8630748/fig2/" target="_blank">2</a>。这是因为,并非所有的数据必须预处理,边缘服务器,更重要的是,可以提高整个系统的鲁棒性。如果边缘分解,云可以继续提供更好的服务。在这项研究中,我们遵守边缘计算范式,如图<a href="//www.newsama.com/journals/scn/2020/8630748/fig2/" target="_blank">2</a>在Android恶意软件检测系统的设计。</p> <h4 id="related-work">3所示。相关工作</h4> <p>重新包装的Android应用程序是手机恶意软件的主要来源之一,和广泛的研究已经开展了关于Android恶意软件检测。在本节中,我们将回顾最密切相关的研究。边缘的典型研究计算也回顾了提供更多详细的背景信息。</p> <h5 id="sec3.1">3.1。脱机检测</h5> <p>重新包装的Android应用程序和恶意软件可以有效地检测到通过代码比较上年。DroidMoss [<a href="#B25">25</a>)侧重于应用程序代码,进行成对相似性比较的检测在Android市场重新打包应用程序。检测结果表明,5%到13%的应用托管在第三方市场被重新包装。然而,两两比较的方法不能扩大,因为数以百万计的Android应用程序现在可以在市场。为了解决这个问题,邵et al。<a href="#B26">26</a>)提出了检测ResDroid重新打包的应用程序在Android市场通过各个击破的策略。首先,他们建立了一个<我>k d</我>树和插入到集群中含有一个或多个应用程序<我>k d</我>树。然后,应用程序中与他们的邻居<我>k d</我>树,比较的数量减少。假设应用程序从官方市场良性,Massvet [<a href="#B27">27</a>提前从安卓市场下载所有应用程序和构建<我>v-core</我>(查看图的几何中心)<我>m-core</我>(Java方法的特征映射到一个索引)数据库重新包装Android恶意软件检测。两个数据库被用来审查提交的新的应用市场。新应用程序将报道为恶意,如果他们重新包装<我>v-cores</我>或<我>m-cores</我>类似于记录在数据库和代码是不合法的重用。</p> <p>除了代码相比,行为和基于ui的检测方法也正在出现。DroidChain [<a href="#B28">28</a>构造一个行为链模型,由Android应用程序的典型行为过程的检测恶意软件。在DroidChain,典型的行为包括隐私泄漏,短信金融收费,恶意软件安装和升级特权。根据田et al。<a href="#B29">29日</a>),重新包装的恶意软件是很难发现,部分原因是良性的应用程序行为的相似之处。要解决这个问题,他们提出了一个新的重新包装Android恶意软件检测技术是基于代码的异质性分析。应用程序的代码结构被分割成多个dependence-based地区,和每个区域独立分类根据其行为特征。De洛伦佐et al。<a href="#B30">30.</a>)提出了可视化VizMal Android应用程序的执行跟踪和突出显示潜在的恶意行为。林等。<a href="#B31">31日</a>)提出了检测重新打包的Android应用程序基于静态UI功能。他们发现3723重新打包应用程序对Anzhi市场和15856年重新包装对Mi市场。这些结果说明重新包装恶意软件仍然对手机用户的安全构成了严重威胁,尽管提出了各种类型的检测方法和采用Android市场(<a href="#B32">32</a>]。</p> <p>最近,一些基于网络的方法已经提出了重新打包应用程序和恶意软件的检测。Arora和Peddoju<a href="#B33">33</a>)展示了使用网络流量检测Android恶意软件的有效性。吴et al。<a href="#B34">34</a>)应用HTTP流量分为2类:主模块交通流量和非基本模块。主要模块的流量,HTTP流距离算法和匈牙利方法被用来计算交通相似性和识别类似的应用对。CREDROID [<a href="#B35">35</a>)确定恶意程序的基础上域名服务器(DNS)查询和数据传输到远程服务器。Zulkifli et al。<a href="#B36">36</a>)提出了一个Android恶意软件检测方法基于七个网络流量特性和J48决策树算法。陈等人。<a href="#B37">37</a>gravitation-based]介绍了不平衡数据分类算法的分类不平衡数据的恶意软件。他等。<a href="#B14">14</a>,<a href="#B38">38</a>)提出了识别加密应用程序通过交通流的相关性和重新包装的检测Android应用程序通过网络行为的比较相似的应用程序。在这些方法中,检测主要是在路由器或网络进行监测节点;因此,移动设备的性能不受影响。然而,网络行为的恶意软件必须提前进行建模,在实践中是具有挑战性的。</p> <h5 id="sec3.2">3.2。设备内置检测</h5> <p>Android恶意软件的检测也可以进行用户的移动设备(<a href="#B39">39</a>]。Alzaylaee et al。<a href="#B40">40</a>)从实际设备中提取特征并使用深度学习系统来检测恶意的Android应用程序。Shamili et al。<a href="#B41">41</a>)提出了一个分布式支持向量机(SVM)算法对Android恶意软件的检测网络上的移动设备。检测功能包括短期调用,媒介时间电话,和即将离任的SMS(短消息服务),等等。实验结果表明,在训练阶段每个客户的平均计算时间是将近10秒。赵et al。<a href="#B42">42</a>)实施了恶意软件检测框架,即RobotDroid,使用一个支持向量机主动学习算法。RobotDroid监控所有正在运行的应用程序来识别他们的运行特点。这些特征后输入学习模块生成的行为特征分类正常的应用程序和恶意软件。根据他们的绩效评估,访问时GPS是女士从80增加到近120 ms检测系统时执行。因此,智能手机的性能,利用这个框架将显著退化。Shabtai et al。<a href="#B8">8</a>]监控应用程序的移动设备的网络行为检测重新包装Android恶意软件,检测精度超过80%;然而,他们的方法的性能开销不是可以忽略不计。例如,它需要7272 kB<svg height="7.35473pt" id="M3" style="vertical-align:-0.3499303pt" version="1.1" viewbox="-0.0498162 -7.0048 7.75925 7.35473" width="7.75925pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g117-37"></use> </g> </svg>15内存消耗和13%<svg height="7.35473pt" id="M4" style="vertical-align:-0.3499303pt" version="1.1" viewbox="-0.0498162 -7.0048 7.75925 7.35473" width="7.75925pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g117-37"></use> </g> </svg>1.5学习的CPU消耗10 Android恶意软件检测模型。</p> <p>为了进一步提高设备内置的性能检测,Crowdroid [<a href="#B10">10</a>)发送检测功能到一个集中的服务器进行处理。Crowdroid只记录了系统调用检测功能,它是轻量级的。现场et al。<a href="#B43">43</a>]提出的APK审计师,这是一个系统,使用权限为Android恶意软件检测静态分析功能。APK审计包括三个部分:(1)签名数据库;(2)一个Android客户端;和(3)一个中央服务器上。Android应用程序客户端发送到中央服务器进行分析。中央服务器提取权限请求的应用和计算允许恶意软件得分基于恶意软件的权限。如果分数超过某一阈值,应用划分为恶意软件。结果表明,特异性的APK审计师达到92.5%;但是,它缺乏动态分析的好处,因为它不能检测动态恶意载荷。</p> <p>莫奈(<a href="#B17">17</a>)也使用后端服务器和客户端应用程序来检测Android恶意软件。客户端应用程序构建一个有向图的应用组件和系统组件,它记录了有潜在危险的系统调用检测功能。这些特性是转发到后端服务器,进行进一步检测通过应用签名匹配算法并返回检测结果。实验结果表明,莫奈可以检测Android恶意软件预测的准确率为99%。然而,莫奈的性能开销很高。所示(<a href="#B17">17</a>),莫奈对内存和I / O开销8%基准和电池5.5%的开销。最近,艾尔沙德et al。<a href="#B44">44</a>SAMADroid提议,这是一个三层混合模式为Android恶意软件的检测。同样,SAMADroid客户端应用程序和分析服务器。客户端应用钩子<我>Strace</我>工具痕迹的系统调用用户应用程序。如果用户调用的应用程序仍然运行在设备上,客户端应用程序继续追踪用户程序的系统调用,生成的日志文件系统调用。后,日志文件发送到SAMADroid服务器与用户应用程序的标识符,在服务器相同的用户应用程序下载商店和静态分析。然后,静态特性和动态特性从日志文件中提取嵌入到一个向量空间。最后,提供的功能是作为输入到机器学习分类的工具。他们的实验结果表明,随机森林产量99.07%的准确率在82.76%的静态特性和动态特性。的性能开销SAMADroid CPU,内存为0.6%,1.8%。在以前的工作<a href="#B45">45</a>),我们使用移动边缘计算检测恶意程序。我们扩展边缘计算模式和改进的聚类方法研究。</p> <h5 id="sec3.3">3.3。边缘计算研究</h5> <p>边缘的愿景和挑战计算介绍了文献[<a href="#B24">24</a>]。边缘计算的基本策略是部署云计算在网络的边缘完善物联网(性能和创建新的应用程序<a href="#B46">46</a>]。然而,边缘的部署位置和边的功能是有争议的。因此,在应用程序中,边缘计算可以实现为雾计算(<a href="#B47">47</a>),移动边缘计算(<a href="#B48">48</a>,<a href="#B49">49</a>),和移动云计算<a href="#B50">50</a>]。在雾中计算范式,分析当地的信息进行“地面”,协调和全球“云进行分析。“一个可以认为所有对象以外的云构成地面;因此,雾计算是计算几乎一样的优势。</p> <p>移动边缘计算部署云服务在移动网络的边缘如5克。即边缘部署在靠近eNodeB,循环流量通过移动边缘计算服务器进行进一步的数据处理。因此,在移动计算边缘,边缘是固定的,和边缘服务器可以由电信公司提供。移动云计算主要关注移动代表团:移动设备应代表批量数据的存储和计算密集型任务的执行到远程实体。远程实体可以是一个集中的云或另一个移动设备。因此,边缘可以由移动云计算的移动设备。因此,最活跃的研究领域之一,在移动云计算领域的任务委托给外部服务,尤其是对其他移动设备。任务代表团也是必不可少的边缘计算(<a href="#B51">51</a>]。</p> <p>在这项研究中,我们提供了一个轻量级的、高效的框架来重新包装Android恶意软件的检测是基于边缘计算。在拟议的框架中,移动设备只需要记录起始时间流,流协议,服务器端IP地址,服务器端端口,每个网络流应用程序名称和版本。之后,这些数据被发送到边缘服务器的流量标记。由于大量的数据保存和发送很小,移动设备的性能没有明显退化。标签的边缘服务器提取检测特征应用网络流量和发送提取的特征到云计算集群。聚类后,可以有效区分原始和打包的应用程序。在我们的研究中,只有网络流量被认为是Android恶意软件检测。相比以前的基于网络的方法如(<a href="#B14">14</a>,<a href="#B34">34</a>- - - - - -<a href="#B36">36</a>),我们不需要模型应用的网络行为提前和我们的方法在实践中更有用。</p> <h4 id="framework-for-android-malware-detection">4所示。Android恶意软件检测的框架</h4> <p>Android的设备内置检测恶意软件是具有挑战性的,因为移动设备通常具有有限的资源。缓解存储和计算的局限性和延长移动设备的寿命,在这项研究中,我们提出一个新的框架重新包装设备上检测的Android恶意软件。拟议的框架如图<a href="//www.newsama.com/journals/scn/2020/8630748/fig3/" target="_blank">3</a>。</p> <div class="floats-partial-section partial-carousel-wrapper" data-section="fig3"> <div class="floats-partial-content fig-content-fig3"> <div class="partial-carousel--single-image"> <img alt="" name="8630748.fig.003" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.003.svgz"> <br> <strong></strong> </div> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">图3</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/fig3/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 设备内置android恶意软件检测框架,基于边缘计算。移动设备发送流的元,如应用程序名称和服务器端IP地址、边缘。边缘服务器捕获应用程序的网络流量和提取HTTP内容和流捕获流量的统计特性。后,发送到云的特性为恶意软件检测。云也与移动设备交互返回检测结果。</d我v> </div> </div> <p>我们的框架由三层组成:移动设备,边缘和云。首先,我们解释了可能的边缘的位置;后来,我们引入了每个组件的功能。在我们的框架,唯一的要求就是它可以监视和处理移动网络流量。移动设备可以连接到互联网通过WiFi或3 g / 4 g;因此,边缘节点可以无线网关,家庭安全网关BitDefender盒和LTE eNodeBs等。边缘节点也可以是位于骨干网路由器如果他们能遵守交通所产生的移动设备。因此,边缘节点的部署位置是灵活的。图<a href="//www.newsama.com/journals/scn/2020/8630748/fig4/" target="_blank">4</a>说明了边缘的部署场景。</p> <div class="floats-partial-section partial-carousel-wrapper" data-section="fig4"> <div class="floats-partial-content fig-content-fig4"> <div class="partial-carousel--single-image"> <img alt="(一)" name="8630748.fig.004a" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.004a.svgz"> <br> <strong>(一)</strong> </div> <div class="partial-carousel--single-image"> <img alt="(b)" name="8630748.fig.004b" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.004b.svgz"> <br> <strong>(b)</strong> </div> <div class="partial-carousel--single-image"> <img alt="(c)" name="8630748.fig.004c" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.004c.svgz"> <br> <strong>(c)</strong> </div> </div> <div class="floats-partial-middle"> <div class="floats-partial-middle--thumbs fig-thumbs-fig4"> <button class="partial-carousel-dot" aria-label="(a)"><img alt="(一)" name="8630748.fig.004a" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.004a.svgz"><br><strong>(一)</strong></button> <button class="partial-carousel-dot" aria-label="(b)"><img alt="(b)" name="8630748.fig.004b" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.004b.svgz"><br><strong>(b)</strong></button> <button class="partial-carousel-dot" aria-label="(c)"><img alt="(c)" name="8630748.fig.004c" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.004c.svgz"><br><strong>(c)</strong></button> </div> <div class="partial-carousel-next-prev fig-nav-fig4"> <button class="carousel-prev" aria-label="Previous"></button> <button class="carousel-next" aria-label="Next"></button> </div> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">图4</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/fig4/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 可能部署的优势。可以无线网关或边缘的专用服务器连接到eNodeB或路由器。(一)无线网关。(b) eNodeB +服务器。(c)路由器+服务器。</d我v> </div> </div> <p>在拟议的框架中,移动设备必须收集和发送流metaformation边缘进行数据预处理。为此,edge-client应用程序被设计为在移动设备上运行。edge-client应用程序是一个Android VPN应用。其主要目标是收集和传输流的元,其中包括应用程序的名称,起始时间,和流协议,以反复的边缘。流的元,边缘服务器进行预处理的网络流量通过添加一个标签为每个流(应用程序名称)。之后,它从这些标记流提取检测特征。交通标识和特征提取部分中详细说明<a href="#sec5.2">5.2</a>。一旦已完成特征提取,边缘服务器发送这些特性到云上。与接收到的特性,云进行恶意软件检测任务和通知移动设备的检测结果。</p> <p>进一步说明该框架的优点,我们比较它与可用的框架。自提出框架是基于边缘的计算,我们将把它作为edge-computing-based框架在下面。同样的,可用的框架称为云计算框架(服务器端部分中描述的检测方法<a href="#sec1">1</a>)和基于网络的框架(基于网络的方法,介绍了部分<a href="#sec1">1</a>和<a href="#sec3">3</a>)分化。而流行的云计算框架(图<a href="//www.newsama.com/journals/scn/2020/8630748/fig5/" target="_blank">5(一个)</a>),edge-computing-based框架的最突出的优点是,特征提取过程是将边缘和移动设备必须保存和传输流的元。因此,提出了移动设备lubuntu edge-computing-based框架。</p> <div class="floats-partial-section partial-carousel-wrapper" data-section="fig5"> <div class="floats-partial-content fig-content-fig5"> <div class="partial-carousel--single-image"> <img alt="(一)" name="8630748.fig.005a" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.005a.svgz"> <br> <strong>(一)</strong> </div> <div class="partial-carousel--single-image"> <img alt="(b)" name="8630748.fig.005b" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.005b.svgz"> <br> <strong>(b)</strong> </div> </div> <div class="floats-partial-middle"> <div class="floats-partial-middle--thumbs fig-thumbs-fig5"> <button class="partial-carousel-dot" aria-label="(a)"><img alt="(一)" name="8630748.fig.005a" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.005a.svgz"><br><strong>(一)</strong></button> <button class="partial-carousel-dot" aria-label="(b)"><img alt="(b)" name="8630748.fig.005b" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.005b.svgz"><br><strong>(b)</strong></button> </div> <div class="partial-carousel-next-prev fig-nav-fig5"> <button class="carousel-prev" aria-label="Previous"></button> <button class="carousel-next" aria-label="Next"></button> </div> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">图5</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/fig5/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 可用框架为android恶意软件检测。各种方法,如<a href="#B10">10</a>),向远程服务器发送提取的特征除了云。我们仍然认为他们是基于云的框架后,因为没有恶意软件检测的本质区别。(b)所示,检测结果通常是提供给网络管理员,不反馈到移动设备。(一)框架基于云。(2)基于网络的框架。</d我v> </div> </div> <p>基于网络的框架(图<a href="//www.newsama.com/journals/scn/2020/8630748/fig5/" target="_blank">5 (b)</a>)移动设备监控网络流量没有任何干扰。然而,它是不准确,因为网络节点不能精确知道网络流的起源,也就是说,它不能识别应用流量有100%的准确度。在文献[演示<a href="#B14">14</a>),由于网络节点不能确定每个流的应用程序(例如,一些流缺乏签名或加密),应用程序的网络行为是不完整的,恶意软件检测精度降低。提出edge-computing-based框架,我们设计一个轻量级edge-client应用收集应用程序信息。此外,可以更好的保护手机用户的隐私在计划的框架。通过部署自己的边缘服务器,移动用户可以控制的类型信息,可以作为检测功能。相比之下,在基于网络的框架中,网络节点可以观察到完整的交通内容和提取任何他们想要的信息,这严重威胁到移动用户的隐私。</p> <p>介绍通用体系结构后,我们轮廓检测方法,可用于edge-computing-based框架。云计算可以使用各种方法来检测Android恶意软件。例如,它可以使用传统的签名匹配(<a href="#B35">35</a>)和网络行为分析(<a href="#B8">8</a>,<a href="#B14">14</a>)来识别恶意程序。然而,这些类型的方法需要先验信息(如签名或行为模型)。在本文中,我们提出一个新颖的重新包装的恶意软件检测方法,集群的网络流量是由相同的应用程序从不同的移动设备。图<a href="//www.newsama.com/journals/scn/2020/8630748/fig6/" target="_blank">6</a>提出了这一过程的一个例子。</p> <div class="floats-partial-section partial-carousel-wrapper" data-section="fig6"> <div class="floats-partial-content fig-content-fig6"> <div class="partial-carousel--single-image"> <img alt="" name="8630748.fig.006" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.006.svgz"> <br> <strong></strong> </div> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">图6</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/fig6/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 说明重新包装的恶意软件检测的交通集群。平原圆圈表示原始应用程序和圆圈和三角形和倒三角形重新包装的。</d我v> </div> </div> <p>背后的动机交通集群有两方面:首先,多数Android恶意软件是由重新包装流行的应用程序(<a href="#B4">4</a>),和流行的应用程序经常是广泛分布的。第二,网络流量产生的重新包装产生的恶意软件不同于原始的应用程序(如部分<a href="#sec2.1">2.1</a>)。如图<a href="//www.newsama.com/journals/scn/2020/8630748/fig3/" target="_blank">3</a>,许多移动设备将连接到云的恶意软件检测。因此,云计算可以观察到两个原始应用程序的网络流量特性及其与大概率重新打包的版本由于流行的应用程序的广泛分布和大量的移动设备。如果我们认为原始应用程序的特点是正常数据和重新打包的版本的特性的异常数据,重新包装的恶意软件检测问题转化为<我>异常检测问题</我>。聚类是一种有效的方法来解决这个问题(<a href="#B52">52</a>]。通过集群应用程序的网络流量特性,我们不需要模型应用的网络行为,而且,更重要的是,我们可以检测各种重新包装原始版本的应用程序,如图<a href="//www.newsama.com/journals/scn/2020/8630748/fig6/" target="_blank">6</a>。的细节提出恶意软件检测方法将详细描述部分<a href="#sec5.3">5.3</a>- - - - - -<a href="#sec5.5">5.5</a>。</p> <h4 id="methodology">5。方法</h4> <p>在本节中,我们介绍的技术细节提出了Android恶意软件检测聚类方法。表<a href="//www.newsama.com/journals/scn/2020/8630748/tab1/" target="_blank">1</a>本文定义了我们使用的主要符号。</p> <div class="floats-partial-section partial-other-wrapper" data-section="tab1"> <div class="floats-partial-content fig-content-tab1"> <table class="table-group" id="tab1"> <tbody> <tr> <td> <table class="table"> <tbody> <tr> <td class="thead-hr" colspan="2"> <hr></td> </tr> <tr class="thead"> <td class="align_left">符号</td> <td class="align_center">意义</td> </tr> <tr> <td class="thead-hr" colspan="2"> <hr></td> </tr> <tr> <td class="align_left"><i>我</我></td> <td class="align_center">安卓应用<我>我</我></td> </tr> <tr> <td class="align_left"><i>u</我></td> <td class="align_center">移动设备的应用程序<我>我</我>安装</td> </tr> <tr> <td class="align_left"><i>r</我></td> <td class="align_center">的设备重新打包应用程序<svg height="8.8423pt" id="M5" style="vertical-align:-0.2064009pt" version="1.1" viewbox="-0.0498162 -8.6359 3.66193 8.8423" width="3.66193pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <path d="M244 607C244 633 228 655 200 655C166 655 146 618 146 594C146 564 166 546 191 546C221 546 244 574 244 607ZM222 91L209 114C184 94 148 66 133 66C127 66 124 73 130 96L201 370C213 416 211 448 191 448C162 448 88 407 29 352L42 328C73 354 104 371 114 371C120 371 119 365 115 345L53 92C32 5 45 -12 68 -12C103 -12 186 50 222 91Z"></path> </g> </svg></td> </tr> <tr> <td class="align_left"><i>f</我></td> <td class="align_center">网络流</td> </tr> <tr> <td class="align_left"><i>C -</我>知识产权<sub><i>f</我></sub></td> <td class="align_center">客户端IP地址的<我>f</我></td> </tr> <tr> <td class="align_left"><i>S -</我>知识产权<sub><i>f</我></sub></td> <td class="align_center">服务器端IP地址的<我>f</我></td> </tr> <tr> <td class="align_left"><i>S -</我>港口<sub><i>f</我></sub></td> <td class="align_center">服务器端港<我>f</我></td> </tr> <tr> <td class="align_left">应用程序<我>N</我><sub><i>f</我></sub></td> <td class="align_center">应用程序生成的名称<我>f</我></td> </tr> <tr> <td class="align_left">应用程序<我>V</我><sub><i>f</我></sub></td> <td class="align_center">版本的应用程序生成<我>f</我></td> </tr> <tr> <td class="align_left"><i>T</我><sub><i>我</我></sub></td> <td class="align_center">设置时间间隔</td> </tr> <tr> <td class="align_left"><span style="width: 13.9518ptpx;"> <svg height="16.1378pt" id="M6" style="vertical-align:-6.18141pt" 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316C44 157 153 -15 402 -15C474 -15 558 5 586 11C604 45 629 119 643 165L614 175Z"></path> </g> <g transform="matrix(.013,0,0,-0.013,8.645,0)"> <path d="M409 504C401 567 396 607 392 642C354 654 312 665 266 665C137 665 60 583 60 487C60 374 161 325 225 290C300 250 355 215 355 141C355 68 311 21 235 21C131 21 86 122 71 183L41 176C48 128 61 42 68 21C78 16 93 8 118 0C142 -7 175 -15 216 -15C349 -15 438 69 438 174C438 287 344 333 265 374C186 414 138 449 138 522C138 576 172 631 249 631C336 631 363 562 380 499L409 504Z"></path> </g> <g transform="matrix(.0091,0,0,-0.0091,14.862,3.132)"> <path d="M538 684C542 703 539 710 529 710C512 710 455 682 363 674L361 644H396C444 644 448 642 438 594L405 438C373 450 347 451 336 451C288 451 200 416 147 374C69 312 24 207 24 113C24 29 60 -12 94 -12C126 -12 156 4 196 30C231 53 296 100 346 166H348L328 81C311 10 325 -12 348 -12C380 -12 450 24 512 98L495 125C466 97 431 70 417 70C408 70 408 80 411 98L538 684ZM390 373L361 240C336 196 210 56 145 56C132 56 113 73 113 131C113 216 156 338 220 379C243 394 266 402 303 402C331 402 375 388 390 373Z"></path> </g> <g transform="matrix(.0065,0,0,-0.0065,19.949,5.233)"> <path d="M256 606C256 635 239 657 207 657C171 657 147 619 147 593C147 563 173 543 194 543C234 543 256 573 256 606ZM233 98L216 125C191 101 156 75 139 75C133 75 132 82 139 107L214 377C226 420 224 454 198 454C169 454 98 415 31 351L46 323C81 353 110 372 116 372C129 372 126 356 121 338L57 101C31 5 47 -12 72 -12C115 -12 197 52 233 98Z"></path> </g> <g transform="matrix(.0065,0,0,-0.0065,21.815,5.233)"> <path d="M490 420C490 437 473 454 444 454C390 454 313 392 258 339L163 247H161L261 676C266 696 264 708 257 708C244 708 183 678 96 672L87 638L131 637C164 636 169 635 161 599L25 -4L33 -12C50 -3 84 5 114 10C127 83 135 123 149 182C155 197 180 221 206 243C235 170 266 105 293 53C320 2 335 -12 363 -12C385 -12 427 -2 489 83L466 109C440 83 414 59 402 59C391 59 382 70 359 113C333 159 293 247 272 296C301 333 360 376 407 376C428 376 444 375 451 369C457 365 470 365 474 372C482 387 490 408 490 420Z"></path> </g> </svg></span></td> <td class="align_center">内容相似<我>d</我><sub><i>我</我></sub>和<我>d</我><sub><i>k</我></sub></td> </tr> <tr> <td class="align_left"><span style="width: 25.2921ptpx;"> <svg height="14.0944pt" id="M11" style="vertical-align:-5.341061pt" version="1.1" viewbox="-0.0498162 -8.75334 25.2921 14.0944" width="25.2921pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <path d="M372 352C427 368 507 407 507 502C507 548 486 592 451 616C420 638 376 650 301 650H44V622C124 616 128 610 128 527V123C128 40 122 34 36 28V0H257C336 0 402 12 453 40C512 72 548 124 548 191C548 291 471 335 372 350V352ZM213 362V558C213 591 216 602 226 608C235 614 258 618 282 618C377 618 415 558 415 490C415 406 369 362 260 362H213ZM213 328H258C380 328 450 283 450 181C450 76 377 35 296 34C231 34 213 53 213 125V328Z"></path> </g> <g transform="matrix(.013,0,0,-0.013,7.644,0)"> <path d="M409 504C401 567 396 607 392 642C354 654 312 665 266 665C137 665 60 583 60 487C60 374 161 325 225 290C300 250 355 215 355 141C355 68 311 21 235 21C131 21 86 122 71 183L41 176C48 128 61 42 68 21C78 16 93 8 118 0C142 -7 175 -15 216 -15C349 -15 438 69 438 174C438 287 344 333 265 374C186 414 138 449 138 522C138 576 172 631 249 631C336 631 363 562 380 499L409 504Z"></path> </g> <g transform="matrix(.0091,0,0,-0.0091,13.858,3.132)"> <path d="M538 684C542 703 539 710 529 710C512 710 455 682 363 674L361 644H396C444 644 448 642 438 594L405 438C373 450 347 451 336 451C288 451 200 416 147 374C69 312 24 207 24 113C24 29 60 -12 94 -12C126 -12 156 4 196 30C231 53 296 100 346 166H348L328 81C311 10 325 -12 348 -12C380 -12 450 24 512 98L495 125C466 97 431 70 417 70C408 70 408 80 411 98L538 684ZM390 373L361 240C336 196 210 56 145 56C132 56 113 73 113 131C113 216 156 338 220 379C243 394 266 402 303 402C331 402 375 388 390 373Z"></path> </g> <g transform="matrix(.0065,0,0,-0.0065,18.945,5.233)"> <path d="M256 606C256 635 239 657 207 657C171 657 147 619 147 593C147 563 173 543 194 543C234 543 256 573 256 606ZM233 98L216 125C191 101 156 75 139 75C133 75 132 82 139 107L214 377C226 420 224 454 198 454C169 454 98 415 31 351L46 323C81 353 110 372 116 372C129 372 126 356 121 338L57 101C31 5 47 -12 72 -12C115 -12 197 52 233 98Z"></path> </g> <g transform="matrix(.0065,0,0,-0.0065,20.81,5.233)"> <path d="M490 420C490 437 473 454 444 454C390 454 313 392 258 339L163 247H161L261 676C266 696 264 708 257 708C244 708 183 678 96 672L87 638L131 637C164 636 169 635 161 599L25 -4L33 -12C50 -3 84 5 114 10C127 83 135 123 149 182C155 197 180 221 206 243C235 170 266 105 293 53C320 2 335 -12 363 -12C385 -12 427 -2 489 83L466 109C440 83 414 59 402 59C391 59 382 70 359 113C333 159 293 247 272 296C301 333 360 376 407 376C428 376 444 375 451 369C457 365 470 365 474 372C482 387 490 408 490 420Z"></path> </g> </svg></span></td> <td class="align_center">行为的相似性<我>d</我><sub><i>我</我></sub>和<我>d</我><sub><i>k</我></sub></td> </tr> <tr> <td class="align_left"><span style="width: 17.5281ptpx;"> <svg height="13.9769pt" id="M12" style="vertical-align:-5.341001pt" version="1.1" viewbox="-0.0498162 -8.6359 17.5281 13.9769" width="17.5281pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <path d="M449 634C442 637 425 643 405 650C376 660 341 666 307 666C181 666 98 590 98 485C98 400 170 343 215 310L246 288C307 243 343 204 343 147C343 67 291 18 219 18C104 18 61 124 51 202L23 199C28 124 27 71 27 47C47 22 122 -16 204 -16C324 -16 428 60 428 174C428 256 379 309 307 360L276 382C223 419 179 455 179 516C179 576 221 632 293 632C379 632 410 564 418 487L448 490C446 536 446 592 449 634Z"></path> </g> <g transform="matrix(.0091,0,0,-0.0091,6.071,3.132)"> <path d="M538 684C542 703 539 710 529 710C512 710 455 682 363 674L361 644H396C444 644 448 642 438 594L405 438C373 450 347 451 336 451C288 451 200 416 147 374C69 312 24 207 24 113C24 29 60 -12 94 -12C126 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206 243C235 170 266 105 293 53C320 2 335 -12 363 -12C385 -12 427 -2 489 83L466 109C440 83 414 59 402 59C391 59 382 70 359 113C333 159 293 247 272 296C301 333 360 376 407 376C428 376 444 375 451 369C457 365 470 365 474 372C482 387 490 408 490 420Z"></path> </g> </svg></span></td> <td class="align_center">最后的相似性<我>d</我><sub><i>我</我></sub>和<我>d</我><sub><i>k</我></sub></td> </tr> <tr class="table-tr"> <td colspan="2"> <hr class="tbody-hr"></td> </tr> </tbody> </table></td> </tr> </tbody> </table> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">表1</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/tab1/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 这篇论文使用的主要符号。</d我v> </div> </div> <h5 id="sec5.1">5.1。系统概述</h5> <p>图<a href="//www.newsama.com/journals/scn/2020/8630748/fig7/" target="_blank">7</a>说明了该方法的主要过程。应用程序<我>我</我>是审查的程序,已经安装了<我>u</我>移动设备。这些<我>u</我>设备连接到<我>e</我>边缘服务器。我们假设<我>r</我>设备已经安装了重新包装恶意软件(恶意软件也提出了应用程序<我>我</我>欺骗用户),<span class="inline_break"> <svg height="11.5564pt" id="M13" style="vertical-align:-2.26807pt" version="1.1" viewbox="-0.0498162 -9.28833 16.751 11.5564" width="16.751pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <path d="M393 379C402 394 400 411 393 422C384 437 365 448 348 448C301 448 237 372 186 285H182L193 335C210 408 205 448 178 448C150 448 80 402 29 344L45 321C80 355 114 373 122 373C128 373 130 365 124 330C106 228 76 98 50 -5L57 -12C82 -5 112 3 132 6L172 203C196 256 234 304 254 329C275 355 293 367 306 367C318 367 330 360 342 348C347 343 355 343 365 350S386 367 393 379Z" id="g113-115"></path> </g> <g transform="matrix(.013,0,0,-0.013,9.12,0)"> <path d="M512 -3V55L134 254V256L512 456V514L75 281V230L512 -3Z" id="g117-91"></path> </g> </svg><span class="irelop"></span> <svg height="11.5564pt" style="vertical-align:-2.26807pt" version="1.1" viewbox="20.3331838 -9.28833 16.094 11.5564" width="16.094pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,20.383,0)"> <path d="M300 -147C201 -63 143 98 143 270S200 602 300 686L282 710C136 610 70 450 70 271V270C70 89 136 -72 282 -170L300 -147Z" id="g113-41"></path> </g> <g transform="matrix(.013,0,0,-0.013,24.881,0)"> <path d="M384 0V27C293 34 287 42 287 114V635C232 613 172 594 109 583V559L157 557C201 555 205 550 205 499V114C205 42 199 34 109 27V0H384Z" id="g113-50"></path> </g> <g transform="matrix(.013,0,0,-0.013,31.121,0)"> <path d="M368 703H309L44 -163H104L368 703Z" id="g113-48"></path> </g> </svg><span class="isep"></span><span class="nowrap"> <svg height="11.5564pt" style="vertical-align:-2.26807pt" version="1.1" viewbox="36.4321838 -9.28833 18 11.5564" width="18pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,36.482,0)"> <path d="M412 140C382 77 369 73 315 73H129L270 222C362 320 402 379 402 466C402 571 322 635 234 635C177 635 130 609 99 576L42 495L64 475C90 514 133 568 201 568C274 568 318 519 318 435C318 349 255 267 193 193C144 135 87 78 32 23V0H405C417 45 427 89 440 131L412 140Z" id="g113-51"></path> </g> <g transform="matrix(.013,0,0,-0.013,42.722,0)"> <path d="M275 270C275 450 212 609 64 710L45 686C145 604 203 442 203 270S147 -63 45 -147L64 -170C213 -68 275 89 275 270Z" id="g113-42"></path> </g> <g transform="matrix(.013,0,0,-0.013,47.22,0)"> <path d="M515 96L502 119C471 88 431 62 423 62C416 62 411 70 417 101C440 223 469 341 497 448H486L412 422L380 277C330 188 210 57 152 57C137 57 126 69 139 124L195 366C210 431 205 448 182 448C155 448 89 413 23 350L36 326C73 354 103 376 112 376C118 376 118 365 113 340L61 118C54 90 52 68 52 51C52 0 75 -12 98 -12S151 -3 181 17C242 58 305 119 362 193H364L345 104C323 3 339 -12 359 -12C390 -12 464 35 515 96Z" id="g113-118"></path> </g> </svg>。</span></span>因此,大部分的设备已经安装了原始版本。这种情况是合理的,因为重新包装Android恶意软件通常是分布在第三方市场,比官方市场不受欢迎(<a href="#B23">23</a>]。因此,下载和安装的数量相对较小。我们将使用这个特征对聚类结果进行分类。</p> <div class="floats-partial-section partial-carousel-wrapper" data-section="fig7"> <div class="floats-partial-content fig-content-fig7"> <div class="partial-carousel--single-image"> <img alt="" name="8630748.fig.007" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.007.svgz"> <br> <strong></strong> </div> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">图7</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/fig7/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 该方法的主要过程为Android恶意软件检测。该方法的核心部分是由围绕数字标记。</d我v> </div> </div> <p>重新包装的恶意软件检测,边缘服务器标签的网络流是由应用程序生成的<我>我</我>据流的元。然后,它提取合适的交通特性(如交通内容和统计)从标记流和发送到云的特性进行处理。因此,有<我>u</我>特性集的应用程序<我>我</我>在云端。这些云过滤器<我>u</我>根据应用程序集版本和删除公共交通。之后,它计算了成对相似性的特性集。最后,集群相似的价值观和标识<我>r</我>重新包装的恶意软件实例。</p> <p>交通标记、特征提取和筛选(标签①,②,③图<a href="//www.newsama.com/journals/scn/2020/8630748/fig7/" target="_blank">7</a>),交通上的相似性计算内容和行为(标签④⑤),和聚类的相似性值(标签⑥)是该方法的核心元素。他们将在以下部分中详细描述。</p> <h5 id="sec5.2">5.2。交通标识、过滤和特征提取</h5> <h6 id="sec5.2.1">5.2.1。交通标识</h6> <p>在这项研究中,交通标识进行识别相应的应用程序为每个网络流,这被称为应用程序识别问题(<a href="#B53">53</a>]。广泛的作品进行了从移动网络流量识别的应用<a href="#B38">38</a>,<a href="#B54">54</a>,<a href="#B55">55</a>]。然而,实现识别精度都低于100%。在我们的方法中,我们设计一个edge-client应用收集流metaformation和准确识别应用。流的元以下定义。</p> <p><span class="statement" id="deff1"><span class="statement-title"><i class="statement-title">定义1(流元)。</我></span>为流<我>f</我>,流的元包括客户端IP地址<我>C -</我>知识产权<sub><i>f</我></sub>流起始时间<我>T</我><sub><i>f</我></sub>流协议<我>P</我><sub><i>f</我></sub>,服务器端IP地址<我>S -</我>知识产权<sub><i>f</我></sub>服务器端端口<我>S -</我>港口<sub><i>f</我></sub>,应用程序的应用程序名称<我>N</我><sub><i>f</我></sub>应用程序,应用程序版本<我>V</我><sub><i>f</我></sub>。流<我>f</我>是双向的,<我>P</我><sub><i>f</我></sub>是传输层协议,如TCP或UDP。<br>edge-client应用类似于一个VPN应用。应用程序发送的流的元边缘服务器在一个固定的时间间隔<我>T</我><sub><i>我</我></sub>。一旦收到了流的元,边缘服务器保存到元数据库和标签可以移动应用流量准确。表示流动观测到边缘服务器<我>f</我><sub><i>u</我></sub>。边缘服务器标签<我>f</我><sub><i>u</我></sub>如下:<span class="list"><span class="list-item"><span class="list-label"></span><span class="list-content">第一步:提取记录时间<svg height="16.1378pt" id="M14" style="vertical-align:-6.18141pt" version="1.1" viewbox="-0.0498162 -9.95639 13.9518 16.1378" width="13.9518pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <path d="M620 675H597C578 656 570 650 541 650H144C112 650 104 653 94 675H72C59 618 42 552 23 493L53 491C71 534 88 564 105 585C124 608 144 615 238 615H290L197 121C182 40 174 34 88 28L82 0H361L367 28C275 34 266 38 281 121L374 615H441C522 615 543 608 553 583C562 560 566 531 565 493L597 494C603 551 612 629 620 675Z" id="g113-85"></path> </g> <g transform="matrix(.0091,0,0,-0.0091,8.285,-5.741)"> <path d="M528 97L513 125C484 95 440 68 431 68C425 68 421 76 427 107C449 227 476 342 505 451H495L418 424L385 278C338 191 220 62 157 62C145 62 133 76 145 130L200 368C215 434 210 451 183 451C157 451 92 418 24 352L37 324C78 356 106 377 115 377C123 377 122 364 116 340L64 115C58 89 56 68 56 52C56 2 78 -12 103 -12C127 -12 159 -4 190 18C247 59 309 113 366 187H368L351 108C328 1 348 -12 368 -12C403 -12 472 33 528 97Z" id="g50-118"></path> </g> <g transform="matrix(.0091,0,0,-0.0091,7.176,3.784)"> <path d="M620 667C620 684 593 710 552 710C515 710 459 687 409 634C360 582 334 506 320 433H247L215 400L220 388H310L259 80C224 -129 199 -161 185 -174C175 -183 160 -192 141 -192C123 -192 90 -181 75 -165C69 -158 64 -156 54 -164C39 -178 24 -195 24 -208C24 -231 61 -257 94 -257C124 -257 162 -243 209 -194C267 -134 303 -66 343 107C369 220 378 279 393 385L503 397L523 433H404C432 619 464 660 500 660C522 660 542 646 566 621C573 614 583 615 593 621C603 628 620 648 620 667Z" id="g50-103"></path> </g> </svg>的<我>f</我><sub><i>u</我></sub>和它的流协议<span class="nowrap"> <svg height="16.1378pt" id="M15" style="vertical-align:-6.18141pt" version="1.1" viewbox="-0.0498162 -9.95639 13.6908 16.1378" width="13.6908pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <path d="M600 480C600 590 528 650 384 650H143L137 622C222 614 225 607 210 531L130 127C113 41 106 36 23 28L17 0H294L300 28C204 36 195 42 212 127L243 284L314 263C327 263 339 263 352 264C465 271 600 337 600 480ZM508 481C508 351 402 304 329 304C289 304 265 311 250 317L295 559C302 594 310 606 323 611C335 616 350 619 367 619C455 619 508 573 508 481Z" id="g113-81"></path> </g> <g transform="matrix(.0091,0,0,-0.0091,8.026,-5.741)"> <use xlink:href="#g50-118"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,6.656,3.784)"> <use xlink:href="#g50-103"></use> </g> </svg>,</span>客户端IP地址<span class="nowrap"> <svg height="16.1378pt" id="M16" style="vertical-align:-6.18141pt" version="1.1" viewbox="-0.0498162 -9.95639 34.6524 16.1378" width="34.6524pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <path d="M645 631C614 643 545 666 457 666C215 666 23 519 23 283C23 90 158 -16 337 -16C412 -16 489 2 522 10C543 39 590 127 606 167L580 181C519 89 459 18 348 18C201 18 122 136 122 287C122 464 244 632 435 632C544 632 602 595 608 472L639 475C643 526 645 581 645 631Z" id="g113-68"></path> </g> <g transform="matrix(.013,0,0,-0.013,8.684,0)"> <path d="M535 230V280H52V230H535Z" id="g117-33"></path> </g> <g transform="matrix(.013,0,0,-0.013,16.315,0)"> <path d="M303 0V28C221 34 213 39 213 125V525C213 610 221 616 303 622V650H38V622C120 616 128 610 128 525V125C128 40 120 34 38 28V0H303Z" id="g190-74"></path> </g> <g transform="matrix(.013,0,0,-0.013,20.748,0)"> <path d="M46 650V622C120 617 128 613 128 525V125C128 42 120 34 40 28V0H311V28C221 34 212 39 212 124V281L286 262C297 261 316 261 331 263C429 275 526 338 526 468C526 533 501 579 462 609C422 638 364 650 293 650H46ZM212 559C212 588 215 600 223 606C230 613 251 618 279 618C361 618 430 572 430 464C430 337 350 302 285 302C252 302 225 309 212 314V559Z" id="g190-81"></path> </g> <g transform="matrix(.0091,0,0,-0.0091,28.14,-5.741)"> <use xlink:href="#g50-118"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,28.14,3.784)"> <use xlink:href="#g50-103"></use> </g> </svg>,</span>服务器端IP地址<span class="nowrap"> <svg height="16.1378pt" id="M17" style="vertical-align:-6.18141pt" version="1.1" viewbox="-0.0498162 -9.95639 32.0948 16.1378" width="32.0948pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <path d="M449 634C442 637 425 643 405 650C376 660 341 666 307 666C181 666 98 590 98 485C98 400 170 343 215 310L246 288C307 243 343 204 343 147C343 67 291 18 219 18C104 18 61 124 51 202L23 199C28 124 27 71 27 47C47 22 122 -16 204 -16C324 -16 428 60 428 174C428 256 379 309 307 360L276 382C223 419 179 455 179 516C179 576 221 632 293 632C379 632 410 564 418 487L448 490C446 536 446 592 449 634Z" id="g113-84"></path> </g> <g transform="matrix(.013,0,0,-0.013,6.136,0)"> <use xlink:href="#g117-33"></use> </g> <g transform="matrix(.013,0,0,-0.013,13.767,0)"> <use xlink:href="#g190-74"></use> </g> <g transform="matrix(.013,0,0,-0.013,18.2,0)"> <use xlink:href="#g190-81"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,25.592,-5.741)"> <use xlink:href="#g50-118"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,25.592,3.784)"> <use xlink:href="#g50-103"></use> </g> </svg>,</span>和服务器端端口<span class="nowrap"> <svg height="16.1378pt" id="M18" style="vertical-align:-6.18141pt" version="1.1" viewbox="-0.0498162 -9.95639 42.6773 16.1378" width="42.6773pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-84"></use> </g> <g transform="matrix(.013,0,0,-0.013,6.136,0)"> <use xlink:href="#g117-33"></use> </g> <g transform="matrix(.013,0,0,-0.013,13.767,0)"> <use xlink:href="#g190-81"></use> </g> <g transform="matrix(.013,0,0,-0.013,20.669,0)"> <path d="M257 449C165 449 37 374 37 209C37 98 119 -12 256 -12C355 -12 473 65 473 226C473 349 381 449 257 449ZM244 416C333 416 380 320 380 204C380 67 329 21 267 21C184 21 130 115 130 241C130 354 184 416 244 416Z" id="g190-112"></path> </g> <g transform="matrix(.013,0,0,-0.013,27.142,0)"> <path d="M181 342V451C133 431 89 419 40 411V388C98 381 102 377 102 311V104C102 38 95 32 33 26V0H263V26C186 32 181 38 181 104V287C203 343 235 372 261 372C277 372 289 366 304 352C310 346 318 345 330 350C349 359 362 379 362 399C362 422 338 449 304 449C256 449 213 393 183 342H181Z" id="g190-115"></path> </g> <g transform="matrix(.013,0,0,-0.013,32.096,0)"> <path d="M298 36L289 62C276 55 253 45 228 45C202 45 169 60 169 141V397H276C289 405 292 426 282 437H169V574L155 576L90 509V437H45L17 408L21 397H90V107C90 28 125 -12 188 -12C198 -12 213 -8 230 1L298 36Z" id="g190-117"></path> </g> <g transform="matrix(.0091,0,0,-0.0091,36.174,-5.741)"> <use xlink:href="#g50-118"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,36.174,3.784)"> <use xlink:href="#g50-103"></use> </g> </svg>。</span></span></span><span class="list-item"><span class="list-label"></span><span class="list-content">第二步:搜索的元数据库<span class="nowrap"> <svg height="16.1378pt" id="M19" style="vertical-align:-6.18141pt" version="1.1" viewbox="-0.0498162 -9.95639 13.6908 16.1378" width="13.6908pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-81"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,8.026,-5.741)"> <use xlink:href="#g50-118"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,6.656,3.784)"> <use xlink:href="#g50-103"></use> </g> </svg>,</span><span class="nowrap"> <svg height="16.1378pt" id="M20" style="vertical-align:-6.18141pt" version="1.1" viewbox="-0.0498162 -9.95639 34.6524 16.1378" width="34.6524pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-68"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.684,0)"> <use xlink:href="#g117-33"></use> </g> <g transform="matrix(.013,0,0,-0.013,16.315,0)"> <use xlink:href="#g190-74"></use> </g> <g transform="matrix(.013,0,0,-0.013,20.748,0)"> <use xlink:href="#g190-81"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,28.14,-5.741)"> <use xlink:href="#g50-118"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,28.14,3.784)"> <use xlink:href="#g50-103"></use> </g> </svg>,</span> <svg height="16.1378pt" id="M21" style="vertical-align:-6.18141pt" version="1.1" viewbox="-0.0498162 -9.95639 32.0948 16.1378" width="32.0948pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-84"></use> </g> <g transform="matrix(.013,0,0,-0.013,6.136,0)"> <use xlink:href="#g117-33"></use> </g> <g transform="matrix(.013,0,0,-0.013,13.767,0)"> <use xlink:href="#g190-74"></use> </g> <g transform="matrix(.013,0,0,-0.013,18.2,0)"> <use xlink:href="#g190-81"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,25.592,-5.741)"> <use xlink:href="#g50-118"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,25.592,3.784)"> <use xlink:href="#g50-103"></use> </g> </svg>,<span class="nowrap"> <svg height="16.1378pt" id="M22" style="vertical-align:-6.18141pt" version="1.1" viewbox="-0.0498162 -9.95639 42.6773 16.1378" width="42.6773pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-84"></use> </g> <g transform="matrix(.013,0,0,-0.013,6.136,0)"> <use xlink:href="#g117-33"></use> </g> <g transform="matrix(.013,0,0,-0.013,13.767,0)"> <use xlink:href="#g190-81"></use> </g> <g transform="matrix(.013,0,0,-0.013,20.669,0)"> <use xlink:href="#g190-112"></use> </g> <g transform="matrix(.013,0,0,-0.013,27.142,0)"> <use xlink:href="#g190-115"></use> </g> <g transform="matrix(.013,0,0,-0.013,32.096,0)"> <use xlink:href="#g190-117"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,36.174,-5.741)"> <use xlink:href="#g50-118"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,36.174,3.784)"> <use xlink:href="#g50-103"></use> </g> </svg>。</span>如果记录匹配,数据库返回的记录最近流起始时间<span class="nowrap"> <svg height="16.1378pt" id="M23" style="vertical-align:-6.18141pt" version="1.1" viewbox="-0.0498162 -9.95639 13.683 16.1378" width="13.683pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-85"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,8.285,-5.741)"> <path d="M397 380C406 395 404 411 396 425S369 451 350 451C302 451 239 372 192 294H189L199 338C214 407 207 451 180 451C152 451 83 405 30 345L48 318C87 354 117 372 125 372S135 362 127 324L55 -5L61 -12C87 -5 117 3 139 5C154 87 168 162 179 207C198 250 240 310 260 332C281 355 297 366 307 366C321 366 333 360 347 346C351 342 360 342 369 348C379 355 389 366 397 380Z" id="g50-115"></path> </g> <g transform="matrix(.0091,0,0,-0.0091,7.176,3.784)"> <use xlink:href="#g50-103"></use> </g> </svg>。</span>否则,该边缘服务器等待一段时间,重复步骤2。</span></span><span class="list-item"><span class="list-label"></span><span class="list-content">步骤3:如果<svg height="16.1378pt" id="M24" style="vertical-align:-6.18141pt" version="1.1" viewbox="-0.0498162 -9.95639 13.9518 16.1378" width="13.9518pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-85"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,8.285,-5.741)"> <use xlink:href="#g50-118"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,7.176,3.784)"> <use xlink:href="#g50-103"></use> </g> </svg>接近<span class="nowrap"> <svg height="16.1378pt" id="M25" style="vertical-align:-6.18141pt" version="1.1" viewbox="-0.0498162 -9.95639 13.683 16.1378" width="13.683pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-85"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,8.285,-5.741)"> <use xlink:href="#g50-115"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,7.176,3.784)"> <use xlink:href="#g50-103"></use> </g> </svg>,</span>边缘服务器标签流<我>f</我><sub><i>u</我></sub>作为<我><</我>应用程序<我>N</我><sub><i>f</我></sub>、应用程序<我>V</我><sub><i>f</我></sub><i>>。</我>否则,等待一段时间,重复步骤2和3。</span></span></span>在上面的步骤中,客户端IP地址<svg height="16.1378pt" id="M26" style="vertical-align:-6.18141pt" version="1.1" viewbox="-0.0498162 -9.95639 34.6524 16.1378" width="34.6524pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-68"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.684,0)"> <use xlink:href="#g117-33"></use> </g> <g transform="matrix(.013,0,0,-0.013,16.315,0)"> <use xlink:href="#g190-74"></use> </g> <g transform="matrix(.013,0,0,-0.013,20.748,0)"> <use xlink:href="#g190-81"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,28.14,-5.741)"> <use xlink:href="#g50-118"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,28.14,3.784)"> <use xlink:href="#g50-103"></use> </g> </svg>用于识别移动设备独有的,这是正确的,当无线网关或eNodeB边缘服务器。在这种情况下,移动设备直接连接到边缘;因此,每个设备的IP地址是独一无二的。然而,如果边缘服务器部署在骨干路由器,如子图中所示(图c)<a href="//www.newsama.com/journals/scn/2020/8630748/fig4/" target="_blank">4</a>,<svg height="16.1378pt" id="M27" style="vertical-align:-6.18141pt" version="1.1" viewbox="-0.0498162 -9.95639 34.6524 16.1378" width="34.6524pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-68"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.684,0)"> <use xlink:href="#g117-33"></use> </g> <g transform="matrix(.013,0,0,-0.013,16.315,0)"> <use xlink:href="#g190-74"></use> </g> <g transform="matrix(.013,0,0,-0.013,20.748,0)"> <use xlink:href="#g190-81"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,28.14,-5.741)"> <use xlink:href="#g50-118"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,28.14,3.784)"> <use xlink:href="#g50-103"></use> </g> </svg>可能是令人困惑,因为移动设备可以位于nat之后(网络地址转换),它们将共享相同的公共IP地址。为了解决这个问题,edge-client应用可以插入特殊指标包独特的代表一个设备。在这项研究中,我们总是假设<svg height="16.1378pt" id="M28" style="vertical-align:-6.18141pt" version="1.1" viewbox="-0.0498162 -9.95639 34.6524 16.1378" width="34.6524pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-68"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.684,0)"> <use xlink:href="#g117-33"></use> </g> <g transform="matrix(.013,0,0,-0.013,16.315,0)"> <use xlink:href="#g190-74"></use> </g> <g transform="matrix(.013,0,0,-0.013,20.748,0)"> <use xlink:href="#g190-81"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,28.14,-5.741)"> <use xlink:href="#g50-118"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,28.14,3.784)"> <use xlink:href="#g50-103"></use> </g> </svg>是独一无二的,我们将在以后的工作中调查device-indicator的实现。<br>在步骤2和3,边缘服务器利用wait-and-repeat策略以确保交通标记是新鲜的和准确的。边缘服务器必须等待,因为移动设备发送的元流动到边缘服务器在一个固定的时间间隔<我>T</我><sub><i>我</我></sub>(60年代在我们的实验),并在数据库中保存的流的元可能是过时的。在我们的实现中,等待时间设置<我>T</我><sub><i>我</我></sub>,如果<span class="inline_break"> <svg height="16.1378pt" id="M29" style="vertical-align:-6.18141pt" version="1.1" viewbox="-0.0498162 -9.95639 58.925 16.1378" width="58.925pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <path d="M162 -163V703H101V-163H162Z" id="g113-9"></path> </g> <g transform="matrix(.013,0,0,-0.013,3.419,0)"> <use xlink:href="#g113-85"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,11.704,-5.741)"> <use xlink:href="#g50-118"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,10.595,3.784)"> <use xlink:href="#g50-103"></use> </g> <g transform="matrix(.013,0,0,-0.013,20.15,0)"> <use xlink:href="#g117-33"></use> </g> <g transform="matrix(.013,0,0,-0.013,30.686,0)"> <use xlink:href="#g113-85"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,38.971,-5.741)"> <use xlink:href="#g50-115"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,37.862,3.784)"> <use xlink:href="#g50-103"></use> </g> <g transform="matrix(.013,0,0,-0.013,44.243,0)"> <use xlink:href="#g113-9"></use> </g> <g transform="matrix(.013,0,0,-0.013,51.294,0)"> <path d="M512 230V281L75 514V456L453 256V254L75 55V-3L512 230Z" id="g117-92"></path> </g> </svg><span class="irelop"></span><span class="nowrap"> <svg height="16.1378pt" style="vertical-align:-6.18141pt" version="1.1" viewbox="62.506183799999995 -9.95639 21.907 16.1378" width="21.907pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,62.556,0)"> <use xlink:href="#g113-51"></use> </g> <g transform="matrix(.013,0,0,-0.013,68.796,0)"> <path d="M456 178V225H360V632H320C217 496 115 347 20 206V178H280V106C280 40 276 34 189 27V0H445V27C364 34 360 39 360 106V178H456ZM280 225H82C149 335 214 431 278 520H280V225Z" id="g113-53"></path> </g> <g transform="matrix(.013,0,0,-0.013,77.212,0)"> <path d="M513 0V26C455 31 447 37 447 103V278C447 398 390 449 309 449C255 449 202 412 166 376V712C127 700 67 684 19 677V653C85 647 87 643 87 580V103C87 37 79 31 19 26L18 0H231V26C171 32 166 39 166 103V341C194 373 232 392 270 392C337 392 368 351 368 269V103C368 38 360 32 302 26V0H513Z" id="g190-105"></path> </g> </svg>,</span></span>返回的流的元被认为是过时了。</span></p> <h6 id="sec5.2.2">5.2.2。交通特征提取</h6> <p>交通标识后,边缘服务器提取检测特征标记的流量。提取的交通特性分为两组:交通内容特征和交通行为的特性。交通内容特征提取的明文内容HTTP流,和交通行为特点是网络流的统计信息,如包大小和间隔。因为Android应用程序可能使用一个加密的HTTPS协议传输数据(<a href="#B54">54</a>)、交通行为特性也必须考虑。交通内容和交通行为特点详细描述部分<a href="#sec5.3">5.3</a>和<a href="#sec5.4">5.4</a>。</p> <h6 id="sec5.2.3">5.2.3。流量过滤</h6> <p>后交通特征提取,提取的边缘服务器发送功能,以及客户端IP地址,服务器端IP地址,服务器端港口、应用程序名称<我>N</我><sub><i>f</我></sub>,应用程序版本<我>V</我><sub><i>f</我></sub>云。注意,应用程序<我>我</我>安装在<我>u</我>设备;因此,云计算的最终<我>u</我>特性集的应用程序<我>我</我>。图<a href="//www.newsama.com/journals/scn/2020/8630748/fig8/" target="_blank">8</a>说明了结构的特性集,云进一步过滤这些<我>u</我>特性集来提高检测精度。首先,它把<我>u</我>设置成<svg height="6.04987pt" id="M30" style="vertical-align:-0.2325001pt" version="1.1" viewbox="-0.0498162 -5.81737 5.98461 6.04987" width="5.98461pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <path d="M219 86C216 168 211 250 206 337C201 410 189 448 163 448C131 448 79 396 43 344L60 322C91 359 110 375 118 375S132 358 136 298C141 238 152 81 155 -12H182C242 62 331 177 390 258C435 321 451 360 451 391C450 424 432 448 408 448C390 448 372 435 366 419C362 410 362 401 366 394C373 383 376 367 376 350C376 283 262 138 221 86H219Z" id="g185-40"></path> </g> </svg>类别根据应用程序版本<我>V</我><sub><i>f</我></sub>。因此,每个类别包含的特性集生成的相同版本的应用程序<我>我</我>。然后,对于每一个类别,云消除了常见的流量特性集。公共交通被定义为网络流中包含所有功能集。这些流有相同的服务器端IP地址和相同的服务器端端口号。这一步的原因是常见的交通会使应用程序之间的相似度计算。否则,特征集之间相似度值都高,他们不能有效地用来区分恶意软件从原始应用程序重新打包。</p> <div class="floats-partial-section partial-carousel-wrapper" data-section="fig8"> <div class="floats-partial-content fig-content-fig8"> <div class="partial-carousel--single-image"> <img alt="" name="8630748.fig.008" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.008.svgz"> <br> <strong></strong> </div> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">图8</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/fig8/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 插图的特性集。集包含客户机IP地址、应用程序名称和应用程序版本。每个网络流是由应用程序生成的<我>我</我>设备是由特征提取的流和服务器的IP地址和端口。</d我v> </div> </div> <p>过滤完成后,计算特性集的相似性,相似性值集群识别恶意软件重新包装。</p> <h5 id="sec5.3">5.3。相似度计算的流量内容</h5> <p>Android应用程序使用HTTP和HTTPS协议主要与他们的远程服务器通信<a href="#B54">54</a>]。对于HTTP流量,因为它是基于明文的,我们可以有效地使用流内容来计算相似度。基本策略是将HTTP流量转换成文档文件、文档和文件可以由信息检索技术相似度计算。HTTP流内容也被用于应用程序识别网络流量(<a href="#B55">55</a>]。然而,在这项研究中,我们只考虑局部HTTP头信息来更好地保护手机用户的隐私。</p> <p>在细节中,首先,我们重组HTTP流从数据包,提取流内容相应的数据包内容保存到一个文本文件为ASCII代码。图<a href="//www.newsama.com/journals/scn/2020/8630748/fig9/" target="_blank">9</a>显示了这样一个例子。然后,我们进行预处理的文本文件删除HTTP请求内容和HTTP请求头,除了得到(或职位)和主机字段。HTTP响应内容也删除,即只有HTTP响应头,得到(或文章),主机在HTTP请求头保存。通过这种方法,移动用户的隐私保护的云(例如,移动电话用户代理(华为)泄露的信息字段,如图<a href="//www.newsama.com/journals/scn/2020/8630748/fig9/" target="_blank">9</a>)。之后,文本文件泄漏使用特殊字符(例如,{/,,,,=,…}),和处理文件成为流内容的功能。</p> <div class="floats-partial-section partial-carousel-wrapper" data-section="fig9"> <div class="floats-partial-content fig-content-fig9"> <div class="partial-carousel--single-image"> <img alt="" name="8630748.fig.009" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.009.svgz"> <br> <strong></strong> </div> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">图9</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/fig9/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 的例子将HTTP流转换为一个文本文件。</d我v> </div> </div> <p>通过改进TF-IDF相似度计算算法(<a href="#B56">56</a>和余弦相似性。这个词在文档中单词计数频率的措施。我们使用增强的频率测量。表示文档(功能设置)<我>d</我><sub><i>我</我></sub>和这个词<span class="nowrap"> <svg height="11.4899pt" id="M31" style="vertical-align:-5.52899pt" version="1.1" viewbox="-0.0498162 -5.96091 13.4899 11.4899" width="13.4899pt" xmlns="http://www.w3.org/2000/svg" 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27.18)" xlink:href="#B33-2"></use> <use transform="matrix(1 0 0 1 43.21 27.18)" xlink:href="#B33-3"></use> </svg></span></span><span class="right_break" id="R33"> <svg class="label" height="11.44pt" id="M33-4" version="1.1" viewbox="0 0 13.398 11.44" width="13.398pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B33-4"> <g transform="matrix(.013,0,0,-0.013,0,9.25)"> <path d="M300 -147C201 -63 143 98 143 270S200 602 300 686L282 710C136 611 70 451 70 272V271C70 90 136 -71 282 -169L300 -147Z" id="g190-41"></path> </g> <g transform="matrix(.013,0,0,-0.013,4.5,9.25)"> <path d="M311 0V25C221 32 216 41 216 113V635C162 613 103 594 39 583V559L88 556C131 552 135 546 135 500V113C135 41 131 32 40 25V0H311Z" id="g190-213"></path> </g> <g transform="matrix(.013,0,0,-0.013,8.9,9.25)"> <path d="M275 271C275 451 212 609 64 710L45 686C145 604 203 442 203 270S147 -63 45 -147L64 -170C213 -68 275 89 275 269V271Z" id="g190-42"></path> </g> </g> </svg> <svg class="alt_label" height="64.4971pt" id="IL33" version="1.1" viewbox="0 0 13.45 64.4971" width="13.45pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <use transform="matrix(1 0 0 1 0 26.32)" xlink:href="#B33-4"></use> </svg></span></span>在哪里<span class="inline_break"> <svg height="14.8173pt" id="M34" style="vertical-align:-5.52897pt" version="1.1" viewbox="-0.0498162 -9.28833 29.171 14.8173" width="29.171pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-103"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.352,0)"> <use xlink:href="#g113-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,12.85,0)"> <use xlink:href="#g113-120"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,21.781,3.132)"> <use xlink:href="#g50-107"></use> </g> <g transform="matrix(.013,0,0,-0.013,26.207,0)"> <use xlink:href="#g113-45"></use> </g> </svg><span class="ipunc"></span> <svg height="14.8173pt" style="vertical-align:-5.52897pt" version="1.1" viewbox="31.300183800000003 -9.28833 14.934 14.8173" width="14.934pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,31.35,0)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,38.5,3.132)"> <use xlink:href="#g50-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,41.556,0)"> <use xlink:href="#g113-42"></use> </g> </svg></span>出现的次数<svg height="11.4899pt" id="M35" style="vertical-align:-5.52899pt" version="1.1" viewbox="-0.0498162 -5.96091 13.4899 11.4899" width="13.4899pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-120"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,8.931,3.132)"> <use xlink:href="#g50-107"></use> </g> </svg>在文档<我>d</我><sub><i>我</我></sub>。</p> <p>逆文档频率词提供的信息量。通常,它是文档的数量的对数比例逆分数包含这个词。逆文档频率<svg height="11.4899pt" id="M36" style="vertical-align:-5.52899pt" version="1.1" viewbox="-0.0498162 -5.96091 13.4899 11.4899" width="13.4899pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-120"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,8.931,3.132)"> <use xlink:href="#g50-107"></use> </g> </svg>是计算<span class="equation_break" id="EEq2"><span class="left_break" id="L37"></span><span class="middle_break"><span class="center_break" id="M37"> <svg height="39.1676pt" id="M37-1" version="1.1" viewbox="0 0 44.629 39.1676" width="44.629pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B37-1"> <g transform="matrix(.013,0,0,-0.013,0,21.946)"> <path d="M244 607C244 633 228 655 200 655C166 655 146 618 146 594C146 564 166 546 191 546C221 546 244 574 244 607ZM222 91L209 114C184 94 148 66 133 66C127 66 124 73 130 96L201 370C213 416 211 448 191 448C162 448 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transform="matrix(.013,0,0,-0.013,11.26,21.946)"> <path d="M238 0V26C174 32 166 38 166 104V712C132 700 70 683 18 677V653C81 647 87 645 87 577V104C87 38 78 32 15 26V0H238Z" id="g121-106"></path> </g> <g transform="matrix(.013,0,0,-0.013,14.55,21.946)"> <path d="M257 449C165 449 37 374 37 209C37 98 119 -12 256 -12C355 -12 473 65 473 226C473 349 381 449 257 449ZM244 416C333 416 380 320 380 204C380 67 329 21 267 21C184 21 130 115 130 241C130 354 184 416 244 416Z" id="g121-109"></path> </g> <g transform="matrix(.013,0,0,-0.013,21.18,21.946)"> <path d="M463 437C426 431 375 425 327 422C297 440 264 449 231 449H230C153 449 51 396 51 283C51 215 94 168 139 149C123 129 91 103 51 88C50 78 53 60 62 46C75 25 100 2 136 -9C112 -28 73 -59 53 -79C38 -94 29 -113 29 -135C30 -192 91 -257 203 -257C336 -257 452 -160 452 -59C452 39 371 59 309 59C275 59 240 58 203 58C158 58 140 77 140 96C140 110 157 129 170 138C186 135 205 133 221 133C306 133 396 185 396 293C396 328 384 360 366 381L423 378C439 387 459 413 468 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transform="matrix(.013,0,0,-0.013,102.31,39.274)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,109.84,21.946)"> <use xlink:href="#g117-36"></use> </g> <g transform="matrix(.013,0,0,-0.013,120.37,21.946)"> <use xlink:href="#g113-49"></use> </g> <g transform="matrix(.013,0,0,-0.013,126.61,21.946)"> <use xlink:href="#g113-47"></use> </g> <g transform="matrix(.013,0,0,-0.013,129.58,21.946)"> <use xlink:href="#g113-49"></use> </g> <g transform="matrix(.013,0,0,-0.013,135.82,21.946)"> <use xlink:href="#g113-50"></use> </g> <g transform="matrix(.013,0,0,-0.013,142.06,21.946)"> <path d="M626 271V272C626 845 478 1358 152 1678L120 1644C380 1367 528 839 528 271C528 -295 377 -825 120 -1102L152 -1136C478 -823 626 -308 626 271Z" id="g119-174"></path> </g> <g transform="matrix(.013,0,0,-0.013,153.91,21.946)"> <use xlink:href="#g113-45"></use> </g> </g> </svg> <svg class="alt_equation" height="66.35pt" id="I37" version="1.1" viewbox="0 0 170.52 66.35" width="170.52pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <use transform="matrix(1 0 0 1 0 -9.46)" xlink:href="#B37-1"></use> <use transform="matrix(1 0 0 1 13.6 27.18)" xlink:href="#B37-2"></use> </svg></span></span><span class="right_break" id="R37"> <svg class="label" height="11.44pt" id="M37-3" version="1.1" viewbox="0 0 15.038 11.44" width="15.038pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B37-3"> <g transform="matrix(.013,0,0,-0.013,0,9.26)"> <use xlink:href="#g190-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,4.5,9.26)"> <path d="M411 139C381 76 368 73 314 73H129L267 224C351 317 400 380 400 469C400 574 322 635 233 635C176 635 128 610 98 576L40 495L63 476C89 515 130 568 198 568C274 568 316 519 316 436C316 347 251 264 191 192C142 134 85 76 30 21V0H403C415 45 425 89 438 131L411 139Z" id="g190-243"></path> </g> <g transform="matrix(.013,0,0,-0.013,10.54,9.26)"> <use xlink:href="#g190-42"></use> </g> </g> </svg> <svg class="alt_label" height="66.35pt" id="IL37" version="1.1" viewbox="0 0 15.1 66.35" width="15.1pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <use transform="matrix(1 0 0 1 0 27.24)" xlink:href="#B37-3"></use> </svg></span></span>在哪里<我>u</我>文档的数量和吗<span class="inline_break"> <svg height="14.8173pt" id="M38" style="vertical-align:-5.52897pt" version="1.1" viewbox="-0.0498162 -9.28833 18.109 14.8173" width="18.109pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-9"></use> </g> <g transform="matrix(.013,0,0,-0.013,3.419,0)"> <path d="M293 -169V-141C218 -131 209 -90 209 -44C209 19 222 85 222 152C222 207 198 255 139 269V273C199 286 222 334 222 388C222 454 209 523 209 588C209 632 218 671 293 681V709C234 709 148 695 148 577C147 513 155 438 155 372C155 337 152 291 64 285V256C152 250 155 204 155 169C156 105 148 31 148 -41C148 -157 234 -169 293 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transform="matrix(.013,0,0,-0.013,47.773,0)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.013,0,0,-0.013,54.988,0)"> <path d="M283 255V284C195 290 192 337 192 375C192 436 200 508 200 580C200 696 116 709 54 709V681C127 671 139 634 139 588C138 524 125 452 125 387C125 333 149 286 209 272V268C148 253 125 206 125 151C126 87 139 16 139 -47C139 -92 127 -131 54 -141V-169C115 -169 200 -152 200 -41C200 32 192 104 192 164C192 202 195 249 283 255Z" id="g113-126"></path> </g> <g transform="matrix(.013,0,0,-0.013,59.499,0)"> <use xlink:href="#g113-9"></use> </g> </svg></span>这个词的文档数量吗<svg height="11.4899pt" id="M39" style="vertical-align:-5.52899pt" version="1.1" viewbox="-0.0498162 -5.96091 13.4899 11.4899" width="13.4899pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-120"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,8.931,3.132)"> <use xlink:href="#g50-107"></use> </g> </svg>出现了。</p> <p>表示由<span class="inline_break"> <svg height="14.8173pt" id="M40" style="vertical-align:-5.52897pt" version="1.1" viewbox="-0.0498162 -9.28833 28.529 14.8173" width="28.529pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <path d="M570 304C570 398 525 448 414 448C385 448 343 445 312 434L329 511L321 518C297 504 262 482 244 460L233 411C195 397 159 381 128 358L135 332C160 347 189 360 224 373L111 -147C97 -210 84 -218 17 -231L13 -257L254 -247L259 -218L233 -216C183 -212 177 -202 189 -142L218 -1C238 -10 266 -12 283 -12C351 3 429 48 483 105C543 168 570 242 570 304ZM482 289C482 161 380 33 304 33C278 33 248 51 233 69L303 396C326 400 352 403 369 403C428 403 482 380 482 289Z" id="g113-113"></path> </g> <g transform="matrix(.013,0,0,-0.013,7.71,0)"> <use xlink:href="#g113-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,12.208,0)"> <use xlink:href="#g113-120"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,21.139,3.132)"> <use xlink:href="#g50-107"></use> </g> <g transform="matrix(.013,0,0,-0.013,25.565,0)"> <use xlink:href="#g113-45"></use> </g> </svg><span class="ipunc"></span> <svg height="14.8173pt" style="vertical-align:-5.52897pt" version="1.1" viewbox="30.6581838 -9.28833 14.936 14.8173" width="14.936pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,30.708,0)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,37.858,3.132)"> <use xlink:href="#g50-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,40.914,0)"> <use xlink:href="#g113-42"></use> </g> </svg></span>的产物<span class="inline_break"> <svg height="14.8173pt" id="M41" style="vertical-align:-5.52897pt" version="1.1" viewbox="-0.0498162 -9.28833 36.477 14.8173" width="36.477pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g 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xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,38.656,0)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,45.806,3.132)"> <use xlink:href="#g50-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,48.862,0)"> <use xlink:href="#g113-42"></use> </g> </svg></span>和<span class="nowrap"> <svg height="14.8173pt" id="M42" style="vertical-align:-5.52897pt" version="1.1" viewbox="-0.0498162 -9.28833 47.8042 14.8173" width="47.8042pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <path d="M405 650H141L135 622C222 616 230 610 215 535L133 116C118 41 113 33 29 28L23 0H289L295 28C209 33 205 40 219 116L298 535C312 609 317 616 399 622L405 650Z" id="g113-74"></path> </g> <g transform="matrix(.013,0,0,-0.013,7.742,0)"> <path d="M743 375C743 570 607 650 407 650H136L130 622C214 612 220 606 204 526L125 122C110 43 105 36 24 27L17 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<p>TF-IDF操作后,所有文件转换成等长数值向量。我们使用余弦相似度来衡量两个文档向量之间的相似度。的文档<我>d</我><sub><i>我</我></sub>和<我>d</我><sub><i>k</我></sub>,相应的数值向量表示<我>V</我>(<我>d</我><sub><i>我</我></sub>),<我>V</我>(<我>d</我><sub><i>k</我></sub>)和向量的长度<我>t</我>。之间的相似性<我>d</我><sub><i>我</我></sub>和<我>d</我><sub><i>k</我></sub>是计算<span class="equation_break" id="EEq4"><span class="left_break" id="L44"></span><span class="middle_break"><span class="center_break" id="M44"> <svg height="43.5754pt" id="M44-1" version="1.1" viewbox="0 0 25.168 43.5754" width="25.168pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B44-1"> <g transform="matrix(.013,0,0,-0.013,0,21.917)"> <path d="M614 175C564 76 510 21 408 21C256 21 146 149 146 336C146 488 235 629 402 629C510 629 570 586 597 480L626 488C620 541 614 582 606 638C578 643 510 665 429 665C206 665 44 527 44 316C44 157 153 -15 402 -15C474 -15 558 5 586 11C604 45 629 119 643 165L614 175Z" id="g190-68"></path> </g> <g transform="matrix(.013,0,0,-0.013,8.65,21.917)"> 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transform="matrix(.0091,0,0,-0.0091,5.811,3.132)"> <use xlink:href="#g50-106"></use> </g> </svg>(我们把<我>u</我>特性集生成的应用程序<我>我</我>在<svg height="6.04987pt" id="M46" style="vertical-align:-0.2325001pt" version="1.1" viewbox="-0.0498162 -5.81737 5.98461 6.04987" width="5.98461pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g185-40"></use> </g> </svg>类别的流量过滤步骤),<我>c</我>特性集。对于每个特性集,我们保存该流特性的HTTP流到一个文本文件<我>c</我>文本文件。然后,我们为每个特性集通过计算数值向量方程(<a href="#EEq3">3</a>)。最后,我们互相比较数值向量方程(<a href="#EEq4">4</a>),并获得<我>c</我>相似度值(<span class="inline_break"> <svg height="14.0944pt" id="M47" style="vertical-align:-5.341061pt" version="1.1" viewbox="-0.0498162 -8.75334 36.129 14.0944" width="36.129pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-68"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.645,0)"> <use 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transform="matrix(.0091,0,0,-0.0091,14.452,3.784)"> <use xlink:href="#g190-111"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,19.256,3.784)"> <use xlink:href="#g190-117"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,21.976,3.784)"> <use xlink:href="#g190-102"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,25.844,3.784)"> <use xlink:href="#g190-111"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,30.648,3.784)"> <use xlink:href="#g190-117"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,33.424,3.784)"> <use xlink:href="#g190-116"></use> </g> </svg>(<我>我</我>= 1,2,…<我>c</我>),结合交通行为的相似度值,将集群识别异常数据点,即重新包装的恶意软件。</p> <h5 id="sec5.4">5.4。相似度计算的交通行为</h5> <p>除了计算流量内容的相似度值,相似的交通行为必须计算由于加密流。我们使用<我>米</我>(<我>米</我>= 11在我们的研究中)统计特性列在表中<a href="//www.newsama.com/journals/scn/2020/8630748/tab2/" target="_blank">2</a>代表一个加密的网络流的行为。流的单位时间和数据包间隔时间毫秒在我们的实验。</p> <div class="floats-partial-section partial-other-wrapper" data-section="tab2"> <div class="floats-partial-content fig-content-tab2"> <table class="table-group" id="tab2"> <tbody> <tr> <td> <table class="table"> <tbody> <tr> <td class="thead-hr" colspan="1"> <hr></td> </tr> <tr> <td class="align_left">应用程序发送的字节数和字节发送的服务器</td> </tr> <tr> <td class="align_left">传出和传入的数据包的数量</td> </tr> <tr> <td class="align_left">均值和std. dev.传出和传入的数据包大小的流持续时间</td> </tr> <tr> <td class="align_left">的均值和std. dev. interpacket时间</td> </tr> <tr class="table-tr"> <td colspan="1"> <hr class="tbody-hr"></td> </tr> </tbody> </table></td> </tr> </tbody> </table> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">表2</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/tab2/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 流量统计功能。</d我v> </div> </div> <p>流量统计功能,特性集<我>d</我><sub><i>我</我></sub>,<我>j</我>th加密流可以表示成一个向量在特征空间:<span class="equation_break" id="EEq5"><span class="left_break" id="L51"></span><span class="middle_break"><span class="center_break" id="M51"> <svg height="19.6661pt" id="M51-1" version="1.1" viewbox="0 0 120.164 19.6661" width="120.164pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B51-1"> <g transform="matrix(.013,0,0,-0.013,0,12.932)"> <use xlink:href="#g113-71"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,7.89,6.033)"> <use xlink:href="#g50-107"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,6.79,17.457)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,11.87,19.558)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,18.39,12.932)"> <use xlink:href="#g117-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,29.65,12.932)"> <use xlink:href="#g119-133"></use> </g> <g transform="matrix(.013,0,0,-0.013,35.44,12.932)"> <use xlink:href="#g113-103"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,43.79,6.668)"> <use xlink:href="#g50-50"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,42.16,16.716)"> <use xlink:href="#g50-107"></use> </g> <g transform="matrix(.013,0,0,-0.013,48.73,12.932)"> <use xlink:href="#g113-45"></use> </g> <g transform="matrix(.013,0,0,-0.013,53.88,12.932)"> <use xlink:href="#g113-103"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,62.23,6.668)"> <use xlink:href="#g50-51"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,60.6,16.716)"> <use xlink:href="#g50-107"></use> </g> <g transform="matrix(.013,0,0,-0.013,67.18,12.932)"> <use xlink:href="#g113-45"></use> </g> <g transform="matrix(.013,0,0,-0.013,72.32,12.932)"> <use xlink:href="#g113-47"></use> </g> <g transform="matrix(.013,0,0,-0.013,77.46,12.932)"> <use xlink:href="#g113-47"></use> </g> <g transform="matrix(.013,0,0,-0.013,82.6,12.932)"> <use xlink:href="#g113-47"></use> </g> <g transform="matrix(.013,0,0,-0.013,87.78,12.932)"> <use xlink:href="#g113-45"></use> </g> <g transform="matrix(.013,0,0,-0.013,92.92,12.932)"> <use xlink:href="#g113-103"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,101.28,6.668)"> <path d="M781 91L765 118C733 86 702 70 693 70C686 70 685 77 692 106L738 297C772 439 736 451 712 451S675 445 647 431C605 410 526 356 452 257H450L459 294C491 426 459 451 429 451C403 451 386 445 361 431C312 404 239 343 170 253H168L188 333C208 411 205 451 175 451C148 451 85 417 24 346L39 318C57 338 100 374 112 374C120 374 122 372 115 339C91 226 62 112 28 -6L37 -12C59 -4 87 3 114 6C125 68 142 127 154 168C184 227 316 383 372 383C397 383 396 366 381 289C362 192 338 92 312 -6L317 -12C339 -5 367 3 396 6L434 170C468 234 598 383 650 383C668 383 676 369 664 319L609 90C593 23 600 -12 629 -12C654 -12 722 23 781 91Z" id="g50-110"></path> </g> <g transform="matrix(.0091,0,0,-0.0091,99.65,16.716)"> <use xlink:href="#g50-107"></use> </g> <g transform="matrix(.013,0,0,-0.013,109.13,12.932)"> <use xlink:href="#g119-134"></use> </g> <g transform="matrix(.013,0,0,-0.013,117.2,12.932)"> <use xlink:href="#g113-45"></use> </g> </g> </svg></span></span><span class="right_break" id="R51"> <svg class="label" height="11.44pt" id="M51-2" version="1.1" viewbox="0 0 14.898 11.44" width="14.898pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B51-2"> <g transform="matrix(.013,0,0,-0.013,0,9.26)"> <use xlink:href="#g190-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,4.5,9.26)"> <path d="M130 550H367L393 615L386 623H101L63 323C82 331 123 342 165 342C275 342 328 277 328 188C328 107 283 40 201 40C141 40 99 72 78 91C69 99 59 98 51 91C39 81 30 67 29 58C28 48 33 37 46 24C60 10 104 -12 149 -12C203 -11 269 14 323 59C384 109 412 165 412 225C412 308 347 399 219 399C193 399 146 382 104 367L130 550Z" id="g190-161"></path> </g> <g transform="matrix(.013,0,0,-0.013,10.4,9.26)"> <use xlink:href="#g190-42"></use> </g> </g> </svg></span></span>在哪里<svg height="18.4396pt" id="M52" style="vertical-align:-6.1814pt" version="1.1" viewbox="-0.0498162 -12.2582 11.4504 18.4396" width="11.4504pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-103"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,8.352,-5.741)"> <use xlink:href="#g50-109"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,6.721,3.784)"> <use xlink:href="#g50-107"></use> </g> </svg>代表的价值<我>l</我>th统计特性,≤1<我>l</我>≤<我>米</我>。图<a href="//www.newsama.com/journals/scn/2020/8630748/fig10/" target="_blank">10</a>显示了一个示例为加密流量的特征表示。因此,交通行为<我>d</我><sub><i>我</我></sub>可以表示成一个矩阵的<span class="nowrap"> <svg height="18.082pt" id="M53" style="vertical-align:-6.4384pt" version="1.1" viewbox="-0.0498162 -11.6436 14.4281 18.082" width="14.4281pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-103"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,8.352,-6.844)"> <path d="M573 302C573 402 527 451 414 451C386 451 343 446 313 437L330 513L320 522C295 508 261 484 243 463L230 415C194 400 159 383 126 359L131 330C159 344 187 357 222 368L109 -147C96 -204 80 -214 18 -223L13 -255L256 -244L259 -212L236 -210C184 -205 180 -195 191 -141L219 -1C240 -10 268 -12 284 -12C352 4 431 48 484 104C543 166 573 240 573 302ZM481 290C481 165 381 37 305 37C280 37 249 56 235 71L302 395C328 399 353 402 372 402C427 402 481 378 481 290Z" id="g50-113"></path> </g> <g transform="matrix(.0091,0,0,-0.0091,6.721,4.041)"> <use xlink:href="#g50-107"></use> </g> </svg>:</span><span class="equation_break" id="EEq6"><span class="left_break" id="L54"></span><span class="middle_break"><span class="center_break" id="M54"> <svg height="21.3651pt" id="M54-1" version="1.1" viewbox="0 0 169.564 21.3651" width="169.564pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B54-1"> <g transform="matrix(.013,0,0,-0.013,0,15.372)"> <path d="M592 498C586 556 582 629 581 675H560C545 656 537 650 510 650H115C87 650 74 652 60 675H40C38 620 33 555 28 495H57C69 539 77 568 89 585C102 607 122 616 205 616H267V123C267 44 259 34 168 28V0H454V28C360 34 352 44 352 123V616H422C498 616 514 608 531 584C542 568 552 543 562 495L592 498Z" id="g190-85"></path> </g> <g transform="matrix(.013,0,0,-0.013,8.02,15.372)"> <path d="M372 352C427 368 507 407 507 502C507 548 486 592 451 616C420 638 376 650 301 650H44V622C124 616 128 610 128 527V123C128 40 122 34 36 28V0H257C336 0 402 12 453 40C512 72 548 124 548 191C548 291 471 335 372 350V352ZM213 362V558C213 591 216 602 226 608C235 614 258 618 282 618C377 618 415 558 415 490C415 406 369 362 260 362H213ZM213 328H258C380 328 450 283 450 181C450 76 377 35 296 34C231 34 213 53 213 125V328Z" id="g190-67"></path> </g> <g transform="matrix(.0091,0,0,-0.0091,15.72,18.503)"> <path d="M504 89L488 119C453 85 428 69 416 69C408 69 405 75 412 102L462 304C492 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</g> <g transform="matrix(.013,0,0,-0.013,59.92,15.372)"> <use xlink:href="#g117-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,71.19,15.372)"> <use xlink:href="#g119-133"></use> </g> <g transform="matrix(.013,0,0,-0.013,76.97,15.372)"> <use xlink:href="#g113-71"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,84.86,9.108)"> <use xlink:href="#g50-50"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,83.75,19.156)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,88.84,21.257)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,91.73,15.372)"> <use xlink:href="#g113-45"></use> </g> <g transform="matrix(.013,0,0,-0.013,96.87,15.372)"> <use xlink:href="#g113-71"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,104.77,9.108)"> <use xlink:href="#g50-51"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,103.66,19.156)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,108.74,21.257)"> <use 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transform="matrix(.0091,0,0,-0.0091,158.03,6.179)"> <path d="M655 676H628C608 656 600 650 571 650H156C118 650 114 651 102 676H77C63 615 45 548 24 485L60 486C81 531 97 562 114 580C134 603 148 611 252 611H308L217 127C201 41 196 38 105 32L98 0H384L393 32C300 38 288 41 304 127L393 611H466C553 611 571 604 582 580C592 559 597 530 595 485L630 489C636 548 645 624 655 676Z" id="g50-85"></path> </g> <g transform="matrix(.013,0,0,-0.013,166.6,15.372)"> <use xlink:href="#g113-45"></use> </g> </g> </svg> <svg class="alt_equation" height="21.3651pt" id="I54" version="1.1" viewbox="0 0 169.56 21.3651" width="169.56pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <use transform="matrix(1 0 0 1 0 0)" xlink:href="#B54-1"></use> </svg></span></span><span class="right_break" id="R54"> <svg class="label" height="11.44pt" id="M54-2" version="1.1" viewbox="0 0 15.428 11.44" width="15.428pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B54-2"> <g transform="matrix(.013,0,0,-0.013,0,9.26)"> <use xlink:href="#g190-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,4.49,9.26)"> <path d="M143 344C173 483 265 547 326 576C363 593 402 605 434 611L429 641C389 634 343 623 301 608C195 570 43 456 43 236C43 81 135 -12 245 -12C368 -12 453 88 453 208C453 310 380 393 273 393C253 393 232 386 211 376L143 344ZM234 338C325 338 367 255 367 172C367 102 346 21 264 21C184 21 132 113 132 239C132 267 133 291 138 312C164 327 197 338 234 338Z" id="g190-227"></path> </g> <g transform="matrix(.013,0,0,-0.013,10.93,9.26)"> <use xlink:href="#g190-42"></use> </g> </g> </svg> <svg class="alt_label" height="21.3651pt" id="IL54" version="1.1" viewbox="0 0 15.49 21.3651" width="15.49pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <use transform="matrix(1 0 0 1 0 4.75)" xlink:href="#B54-2"></use> </svg></span></span>在哪里<我>n</我>是中包含加密流的数量吗<我>d</我><sub><i>我</我></sub>和<我>n</我>≥1。</p> <div class="floats-partial-section partial-carousel-wrapper" data-section="fig10"> <div class="floats-partial-content fig-content-fig10"> <div class="partial-carousel--single-image"> <img alt="" name="8630748.fig.0010" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.0010.svgz"> <br> <strong></strong> </div> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">图10</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/fig10/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 的例子一个加密流转换成一个特征向量。</d我v> </div> </div> <p>因为不同的特性集的数量可能有所不同的加密流,交通行为<svg height="14.6294pt" id="M55" style="vertical-align:-5.34107pt" version="1.1" viewbox="-0.0498162 -9.28833 55.5192 14.6294" width="55.5192pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-85"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.021,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,15.724,3.132)"> <use xlink:href="#g50-111"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.337,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,22.708,3.132)"> <use xlink:href="#g54-42"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,28.268,3.132)"> <use xlink:href="#g50-110"></use> </g> <g transform="matrix(.013,0,0,-0.013,36.157,0)"> <use xlink:href="#g113-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,40.655,0)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,47.805,3.132)"> <use xlink:href="#g50-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,50.861,0)"> <use xlink:href="#g113-42"></use> </g> </svg>和<svg height="14.6294pt" id="M56" style="vertical-align:-5.34107pt" version="1.1" viewbox="-0.0498162 -9.28833 59.0984 14.6294" width="59.0984pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-85"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.021,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,15.724,3.132)"> <use xlink:href="#g50-111"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.337,5.233)"> <use xlink:href="#g176-108"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,24.196,3.132)"> <use xlink:href="#g54-42"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,29.756,3.132)"> <use xlink:href="#g50-110"></use> </g> <g transform="matrix(.013,0,0,-0.013,37.645,0)"> <use xlink:href="#g113-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,42.143,0)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,49.293,3.132)"> <use xlink:href="#g50-108"></use> </g> <g transform="matrix(.013,0,0,-0.013,54.44,0)"> <use xlink:href="#g113-42"></use> </g> </svg>可能不同的不同的维度,即价值的<我>n</我><sub><i>我</我></sub>不应该等于的<我>n</我><sub><i>k</我></sub>。有效地计算相似性<svg height="14.6294pt" id="M57" style="vertical-align:-5.34107pt" version="1.1" viewbox="-0.0498162 -9.28833 55.5192 14.6294" width="55.5192pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-85"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.021,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,15.724,3.132)"> <use xlink:href="#g50-111"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.337,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,22.708,3.132)"> <use xlink:href="#g54-42"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,28.268,3.132)"> <use xlink:href="#g50-110"></use> </g> <g transform="matrix(.013,0,0,-0.013,36.157,0)"> <use xlink:href="#g113-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,40.655,0)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,47.805,3.132)"> <use xlink:href="#g50-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,50.861,0)"> <use xlink:href="#g113-42"></use> </g> </svg>和<span class="nowrap"> <svg height="14.6294pt" id="M58" style="vertical-align:-5.34107pt" version="1.1" viewbox="-0.0498162 -9.28833 59.0984 14.6294" width="59.0984pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-85"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.021,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,15.724,3.132)"> <use xlink:href="#g50-111"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.337,5.233)"> <use xlink:href="#g176-108"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,24.196,3.132)"> <use xlink:href="#g54-42"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,29.756,3.132)"> <use xlink:href="#g50-110"></use> </g> <g transform="matrix(.013,0,0,-0.013,37.645,0)"> <use xlink:href="#g113-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,42.143,0)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,49.293,3.132)"> <use xlink:href="#g50-108"></use> </g> <g transform="matrix(.013,0,0,-0.013,54.44,0)"> <use xlink:href="#g113-42"></use> </g> </svg>,</span>弗罗贝尼乌斯范数的计算<svg height="14.6294pt" id="M59" style="vertical-align:-5.34107pt" version="1.1" viewbox="-0.0498162 -9.28833 55.5192 14.6294" width="55.5192pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-85"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.021,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,15.724,3.132)"> <use xlink:href="#g50-111"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.337,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,22.708,3.132)"> <use xlink:href="#g54-42"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,28.268,3.132)"> <use xlink:href="#g50-110"></use> </g> <g transform="matrix(.013,0,0,-0.013,36.157,0)"> <use xlink:href="#g113-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,40.655,0)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,47.805,3.132)"> <use xlink:href="#g50-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,50.861,0)"> <use xlink:href="#g113-42"></use> </g> </svg>和<span class="nowrap"> <svg height="14.6294pt" id="M60" style="vertical-align:-5.34107pt" version="1.1" viewbox="-0.0498162 -9.28833 59.0984 14.6294" width="59.0984pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-85"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.021,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,15.724,3.132)"> <use xlink:href="#g50-111"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.337,5.233)"> <use xlink:href="#g176-108"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,24.196,3.132)"> <use xlink:href="#g54-42"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,29.756,3.132)"> <use xlink:href="#g50-110"></use> </g> <g transform="matrix(.013,0,0,-0.013,37.645,0)"> <use xlink:href="#g113-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,42.143,0)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,49.293,3.132)"> <use xlink:href="#g50-108"></use> </g> <g transform="matrix(.013,0,0,-0.013,54.44,0)"> <use xlink:href="#g113-42"></use> </g> </svg>。</span>中给出的公式是方程(<a href="#EEq7">7</a>),规范(·)规范化的价值<svg height="18.4396pt" id="M61" style="vertical-align:-6.1814pt" version="1.1" viewbox="-0.0498162 -12.2582 11.4504 18.4396" width="11.4504pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-103"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,8.352,-5.741)"> <use xlink:href="#g50-109"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,6.721,3.784)"> <use xlink:href="#g50-107"></use> </g> </svg>[0,1]:<span class="equation_break" id="EEq7"><span class="left_break" id="L62"></span><span class="middle_break"><span class="center_break" id="M62"> <svg height="45.4571pt" id="M62-1" version="1.1" viewbox="0 0 159.084 45.4571" width="159.084pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B62-1"> <g transform="matrix(.013,0,0,-0.013,0,25.885)"> <path d="M493 503C489 551 484 614 483 650H43V622C120 616 128 611 128 525V126C128 40 120 34 40 28V0H312V28C221 34 213 40 213 126V307H316C407 307 412 296 424 227H453V420H424C412 355 407 346 316 346H213V584C213 613 216 616 246 616H322C398 616 419 607 436 579C449 559 455 539 464 499L493 503Z" id="g190-71"></path> </g> <g transform="matrix(.013,0,0,-0.013,6.87,25.885)"> <path d="M719 650H483V622C553 619 576 606 581 560C585 532 588 487 588 394V148H585L167 650H20V622C67 618 88 610 109 585C127 562 129 557 129 484V264C129 173 126 124 123 93C118 44 92 31 35 28V0H272V28C204 32 181 44 176 95C173 124 170 172 170 264V515H172L598 -9H629V394C629 487 631 532 635 563C639 606 663 619 719 622V650Z" id="g190-79"></path> </g> <g transform="matrix(.013,0,0,-0.013,18.77,26.068)"> <use xlink:href="#g113-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,23.29,25.885)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.013,0,0,-0.013,30.5,26.068)"> <use xlink:href="#g113-42"></use> </g> <g transform="matrix(.013,0,0,-0.013,38.68,25.885)"> <use xlink:href="#g117-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,49.94,26.382)"> <path d="M767 1968H717L614 -968H612L327 324L133 268L144 227L265 262L644 -1458H646L767 1968Z" id="g119-125"></path> </g> <rect height="0.65243" 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transform="matrix(.0091,0,0,-0.0091,77.49,40.018)"> <use xlink:href="#g54-34"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,83.05,40.018)"> <use xlink:href="#g50-50"></use> </g> <g transform="matrix(.013,0,0,-0.013,90.03,17.416)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,90.03,21.018)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,90.03,24.619)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,90.03,28.221)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,90.03,31.822)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,93.47,25.885)"> <use xlink:href="#g190-111"></use> </g> <g transform="matrix(.013,0,0,-0.013,100.52,25.885)"> <use xlink:href="#g190-112"></use> </g> <g transform="matrix(.013,0,0,-0.013,107,25.885)"> <use xlink:href="#g190-115"></use> </g> <g transform="matrix(.013,0,0,-0.013,111.9,25.885)"> <path d="M797 0V26C739 32 732 36 732 103V296C732 394 682 449 605 449C576 449 550 437 529 423C504 407 475 389 446 366C425 418 382 449 334 449C303 449 279 437 253 421C222 403 201 385 180 371V452C135 432 85 419 41 411V388C99 379 102 374 102 310V103C102 38 93 32 27 26V0H238V26C189 32 180 38 180 103V338C210 363 250 390 289 390C351 390 377 348 377 275V103C377 37 368 32 306 26V0H520V26C465 32 456 38 456 101V296C456 314 455 326 453 338C491 369 529 390 565 390C628 390 653 345 653 274V107C653 36 642 32 583 26V0H797Z" id="g190-110"></path> </g> <g transform="matrix(.013,0,0,-0.013,124.83,25.885)"> <use xlink:href="#g119-133"></use> </g> <g transform="matrix(.013,0,0,-0.013,130.61,25.885)"> <use xlink:href="#g113-103"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,138.97,21.224)"> <use xlink:href="#g50-109"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,137.34,29.926)"> <use xlink:href="#g50-107"></use> </g> <g transform="matrix(.013,0,0,-0.013,141.94,25.885)"> <use xlink:href="#g119-134"></use> </g> <g transform="matrix(.013,0,0,-0.013,147.75,17.416)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,147.75,21.018)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,147.75,24.619)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,147.75,28.221)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,147.75,31.822)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,151.18,16.692)"> <use xlink:href="#g50-51"></use> </g> <g transform="matrix(.013,0,0,-0.013,156.12,25.885)"> <use xlink:href="#g113-47"></use> </g> </g> </svg></span></span><span class="right_break" id="R62"> <svg class="label" height="11.44pt" id="M62-2" version="1.1" viewbox="0 0 15.028 11.44" width="15.028pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B62-2"> <g transform="matrix(.013,0,0,-0.013,0,9.26)"> <use xlink:href="#g190-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,4.5,9.26)"> <path d="M430 623H48C43 580 39 534 30 478H57C80 544 84 550 152 550H369C286 366 187 178 74 -1L81 -12L156 -2C249 201 343 408 438 611L430 623Z" id="g190-223"></path> </g> <g transform="matrix(.013,0,0,-0.013,10.53,9.26)"> <use xlink:href="#g190-42"></use> </g> </g> </svg></span></span></p> <p>然后,之间的距离<svg height="14.6294pt" id="M63" style="vertical-align:-5.34107pt" version="1.1" viewbox="-0.0498162 -9.28833 55.5192 14.6294" width="55.5192pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-85"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.021,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,15.724,3.132)"> <use xlink:href="#g50-111"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.337,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,22.708,3.132)"> <use xlink:href="#g54-42"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,28.268,3.132)"> <use xlink:href="#g50-110"></use> </g> <g transform="matrix(.013,0,0,-0.013,36.157,0)"> <use xlink:href="#g113-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,40.655,0)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,47.805,3.132)"> <use xlink:href="#g50-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,50.861,0)"> <use xlink:href="#g113-42"></use> </g> </svg>和<svg height="14.6294pt" id="M64" style="vertical-align:-5.34107pt" version="1.1" viewbox="-0.0498162 -9.28833 59.0984 14.6294" width="59.0984pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-85"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.021,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,15.724,3.132)"> <use xlink:href="#g50-111"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.337,5.233)"> <use xlink:href="#g176-108"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,24.196,3.132)"> <use xlink:href="#g54-42"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,29.756,3.132)"> <use xlink:href="#g50-110"></use> </g> <g transform="matrix(.013,0,0,-0.013,37.645,0)"> <use xlink:href="#g113-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,42.143,0)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,49.293,3.132)"> <use xlink:href="#g50-108"></use> </g> <g transform="matrix(.013,0,0,-0.013,54.44,0)"> <use xlink:href="#g113-42"></use> </g> </svg>是计算<span class="equation_break" id="EEq8"><span class="left_break" id="L65"></span><span class="middle_break"><span class="center_break" id="M65"> <svg height="14.5707pt" id="M65-1" version="1.1" viewbox="0 0 175.644 14.5707" width="175.644pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B65-1"> <g transform="matrix(.013,0,0,-0.013,0,10.593)"> <path d="M517 51L485 54C448 58 441 63 441 115V712C404 700 337 684 285 678V653C357 648 362 645 362 580V437C339 446 309 449 295 449C159 449 38 340 38 201C38 61 143 -12 223 -12C234 -12 261 -6 301 17L362 53V-12C420 9 495 22 517 26V51ZM362 85C338 67 301 51 266 51C201 51 128 109 128 228C128 373 212 411 259 411C296 411 338 395 362 360V85Z" id="g190-101"></path> </g> <g transform="matrix(.013,0,0,-0.013,6.86,10.593)"> <path d="M135 536C164 536 186 560 186 587C186 617 164 639 136 639C109 639 85 617 85 587C85 560 109 536 135 536ZM252 0V26C188 32 181 38 181 106V451C138 433 90 420 39 412V388C99 379 102 374 102 312V106C102 38 95 32 32 26V0H252Z" id="g190-106"></path> </g> <g transform="matrix(.013,0,0,-0.013,10.3,10.593)"> <use xlink:href="#g190-116"></use> </g> <g transform="matrix(.013,0,0,-0.013,17.31,10.593)"> <use xlink:href="#g119-5"></use> </g> <g transform="matrix(.013,0,0,-0.013,22.34,10.593)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,29.49,13.725)"> <use xlink:href="#g50-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,32.54,10.593)"> <use xlink:href="#g113-45"></use> </g> <g transform="matrix(.013,0,0,-0.013,37.68,10.593)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,44.83,13.725)"> <use xlink:href="#g50-108"></use> </g> <g transform="matrix(.013,0,0,-0.013,49.98,10.593)"> <use xlink:href="#g119-6"></use> </g> <g transform="matrix(.013,0,0,-0.013,58.7,10.593)"> <use xlink:href="#g117-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,69.96,3.925)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,69.96,7.527)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,69.96,11.128)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,69.96,14.73)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,73.4,10.593)"> <use xlink:href="#g190-71"></use> </g> <g transform="matrix(.013,0,0,-0.013,80.27,10.593)"> <use xlink:href="#g190-79"></use> </g> <g transform="matrix(.013,0,0,-0.013,92.17,10.593)"> <use xlink:href="#g119-5"></use> </g> <g transform="matrix(.013,0,0,-0.013,97.2,10.593)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,104.35,13.725)"> <use xlink:href="#g50-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,107.4,10.593)"> <use xlink:href="#g119-6"></use> </g> <g transform="matrix(.013,0,0,-0.013,115.36,10.593)"> <use xlink:href="#g117-33"></use> </g> <g transform="matrix(.013,0,0,-0.013,125.9,10.593)"> <use xlink:href="#g190-71"></use> </g> <g transform="matrix(.013,0,0,-0.013,132.77,10.593)"> <use xlink:href="#g190-79"></use> </g> <g transform="matrix(.013,0,0,-0.013,144.67,10.593)"> <use xlink:href="#g119-5"></use> </g> <g transform="matrix(.013,0,0,-0.013,149.7,10.593)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,156.85,13.725)"> <use xlink:href="#g50-108"></use> </g> <g transform="matrix(.013,0,0,-0.013,161.99,10.593)"> <use xlink:href="#g119-6"></use> </g> <g transform="matrix(.013,0,0,-0.013,167.04,3.925)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,167.04,7.527)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,167.04,11.128)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,167.04,14.73)"> <use xlink:href="#g119-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,172.68,10.593)"> <use xlink:href="#g113-47"></use> </g> </g> </svg> <svg class="alt_equation" height="14.5707pt" id="I65" version="1.1" viewbox="0 0 175.65 14.5707" width="175.65pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <use transform="matrix(1 0 0 1 0 0)" xlink:href="#B65-1"></use> </svg></span></span><span class="right_break" id="R65"> <svg class="label" height="11.44pt" id="M65-2" version="1.1" viewbox="0 0 15.168 11.44" width="15.168pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B65-2"> <g transform="matrix(.013,0,0,-0.013,0,9.26)"> <use xlink:href="#g190-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,4.5,9.26)"> <path d="M246 635C138 635 67 554 67 471C67 401 116 348 178 315C143 296 103 268 87 252C65 231 42 203 42 157C42 50 128 -12 234 -12C319 -12 432 52 432 169C432 256 370 303 299 344C347 376 373 399 381 408C399 430 408 459 408 487C408 569 341 635 246 635ZM235 603C284 603 334 567 334 483C334 420 306 383 273 358C202 393 142 427 142 503C142 552 173 603 235 603ZM245 21C179 21 122 70 122 163C122 219 155 270 204 300C279 263 352 219 352 144C352 66 308 21 245 21Z" id="g190-152"></path> </g> <g transform="matrix(.013,0,0,-0.013,10.67,9.26)"> <use xlink:href="#g190-42"></use> </g> </g> </svg> <svg class="alt_label" height="14.5707pt" id="IL65" version="1.1" viewbox="0 0 15.23 14.5707" width="15.23pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <use transform="matrix(1 0 0 1 0 1.35)" xlink:href="#B65-2"></use> </svg></span></span></p> <p>最后,之间的相似性<svg height="14.6294pt" id="M66" style="vertical-align:-5.34107pt" version="1.1" viewbox="-0.0498162 -9.28833 55.5192 14.6294" width="55.5192pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-85"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.021,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,15.724,3.132)"> <use xlink:href="#g50-111"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.337,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,22.708,3.132)"> <use xlink:href="#g54-42"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,28.268,3.132)"> <use xlink:href="#g50-110"></use> </g> <g transform="matrix(.013,0,0,-0.013,36.157,0)"> <use xlink:href="#g113-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,40.655,0)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,47.805,3.132)"> <use xlink:href="#g50-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,50.861,0)"> <use xlink:href="#g113-42"></use> </g> </svg>和<svg height="14.6294pt" id="M67" style="vertical-align:-5.34107pt" version="1.1" viewbox="-0.0498162 -9.28833 59.0984 14.6294" width="59.0984pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-85"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.021,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,15.724,3.132)"> <use xlink:href="#g50-111"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.337,5.233)"> <use xlink:href="#g176-108"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,24.196,3.132)"> <use xlink:href="#g54-42"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,29.756,3.132)"> <use xlink:href="#g50-110"></use> </g> <g transform="matrix(.013,0,0,-0.013,37.645,0)"> <use xlink:href="#g113-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,42.143,0)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,49.293,3.132)"> <use xlink:href="#g50-108"></use> </g> <g transform="matrix(.013,0,0,-0.013,54.44,0)"> <use xlink:href="#g113-42"></use> </g> </svg>可以通过计算<span class="equation_break" id="EEq9"><span class="left_break" id="L68"></span><span class="middle_break"><span class="center_break" id="M68"> <svg height="37.3146pt" id="M68-1" version="1.1" viewbox="0 0 24.158 37.3146" width="24.158pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B68-1"> <g transform="matrix(.013,0,0,-0.013,0,20.093)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.013,0,0,-0.013,7.64,20.093)"> <use xlink:href="#g190-84"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,13.86,23.224)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,18.94,25.325)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.81,25.325)"> <use xlink:href="#g176-108"></use> </g> </g> </svg> <svg height="37.3146pt" id="M68-2" version="1.1" viewbox="0 0 17.5 37.3146" width="17.5pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B68-2"> <g transform="matrix(.013,0,0,-0.013,0,20.093)"> <use xlink:href="#g117-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,11.26,20.093)"> <use xlink:href="#g113-50"></use> </g> </g> </svg> <svg height="37.3146pt" id="M68-3" version="1.1" viewbox="0 0 230.984 37.3146" width="230.984pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B68-3"> <g transform="matrix(.013,0,0,-0.013,0,20.093)"> <use xlink:href="#g117-33"></use> </g> <g transform="matrix(.013,0,0,-0.013,91.74,10.593)"> <use xlink:href="#g190-101"></use> </g> <g transform="matrix(.013,0,0,-0.013,98.61,10.593)"> <use xlink:href="#g190-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,102.05,10.593)"> <use xlink:href="#g190-116"></use> </g> <g transform="matrix(.013,0,0,-0.013,109.06,10.593)"> <use xlink:href="#g119-5"></use> </g> <g transform="matrix(.013,0,0,-0.013,114.08,10.593)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,121.23,13.725)"> <use xlink:href="#g50-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,124.29,10.593)"> <use xlink:href="#g113-45"></use> </g> <g transform="matrix(.013,0,0,-0.013,129.43,10.593)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,136.58,13.725)"> <use xlink:href="#g50-108"></use> </g> <g transform="matrix(.013,0,0,-0.013,141.73,10.593)"> <use xlink:href="#g119-6"></use> </g> <rect height="0.65243" width="215.093" x="11.73" y="16.439"></rect> <g transform="matrix(.013,0,0,-0.013,11.73,31.484)"> <use xlink:href="#g121-107"></use> </g> <g transform="matrix(.013,0,0,-0.013,22.34,31.484)"> <use xlink:href="#g121-95"></use> </g> <g transform="matrix(.013,0,0,-0.013,28.05,31.484)"> <use xlink:href="#g121-118"></use> </g> <g transform="matrix(.013,0,0,-0.013,36.47,31.484)"> <path d="M335 -404V-369L312 -368C205 -360 203 -355 203 -249V751C203 895 206 900 312 908L335 909V944H138V-404H335Z" id="g119-129"></path> </g> <g transform="matrix(.013,0,0,-0.013,41.84,31.484)"> <use xlink:href="#g190-101"></use> </g> <g transform="matrix(.013,0,0,-0.013,48.7,31.484)"> <use xlink:href="#g190-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,52.14,31.484)"> <use xlink:href="#g190-116"></use> </g> <g transform="matrix(.013,0,0,-0.013,59.15,31.484)"> <use xlink:href="#g119-133"></use> </g> <g transform="matrix(.013,0,0,-0.013,64.93,31.484)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,72.08,34.616)"> <use xlink:href="#g50-115"></use> </g> <g transform="matrix(.013,0,0,-0.013,76.48,31.484)"> <use xlink:href="#g113-45"></use> </g> <g transform="matrix(.013,0,0,-0.013,81.62,31.484)"> <use xlink:href="#g113-101"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,88.77,34.616)"> <path d="M481 430L460 436C440 442 393 451 366 451C348 451 325 448 313 446C267 437 195 409 147 367C79 308 24 211 24 105C24 37 56 -12 93 -12C121 -12 156 1 199 32C246 66 313 122 349 168H351L286 -147C274 -205 261 -215 210 -224L199 -226L193 -255L438 -243L442 -214L417 -212C364 -208 359 -200 370 -140L433 204C455 324 469 389 481 430ZM391 385C382 336 366 260 358 238C321 178 209 59 143 59C129 59 115 83 115 131C115 207 152 317 220 373C243 392 282 403 314 403C348 403 374 395 391 385Z" id="g50-114"></path> </g> <g transform="matrix(.013,0,0,-0.013,93.83,31.484)"> <use xlink:href="#g119-134"></use> </g> <g transform="matrix(.013,0,0,-0.013,101.85,31.484)"> <use xlink:href="#g113-45"></use> </g> <g transform="matrix(.013,0,0,-0.013,107,31.484)"> <use xlink:href="#g113-115"></use> </g> <g transform="matrix(.013,0,0,-0.013,112.49,31.484)"> <use xlink:href="#g113-45"></use> </g> <g transform="matrix(.013,0,0,-0.013,117.63,31.484)"> <path d="M474 429L457 433C435 440 389 448 367 448C348 448 323 446 309 443C266 434 195 406 148 366C78 307 23 210 23 101C23 35 55 -12 92 -12C118 -12 146 1 196 35C247 70 311 130 346 173H348L281 -148C268 -211 256 -221 208 -229L191 -232L187 -257L433 -245L437 -219L411 -216C357 -210 350 -205 362 -140L427 207C447 315 461 381 474 429ZM387 387C379 337 363 262 355 236C318 180 201 57 142 57C126 57 112 81 112 128C112 205 150 321 220 376C244 395 280 403 312 403C345 403 370 396 387 387Z" id="g113-114"></path> </g> <g transform="matrix(.013,0,0,-0.013,127.64,31.484)"> <use xlink:href="#g117-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,138.91,31.484)"> <use xlink:href="#g113-50"></use> </g> <g transform="matrix(.013,0,0,-0.013,145.15,31.484)"> <use xlink:href="#g113-45"></use> </g> <g transform="matrix(.013,0,0,-0.013,150.29,31.484)"> <use xlink:href="#g113-51"></use> </g> <g transform="matrix(.013,0,0,-0.013,156.53,31.484)"> <use xlink:href="#g113-45"></use> </g> <g transform="matrix(.013,0,0,-0.013,161.67,31.484)"> <use xlink:href="#g113-47"></use> </g> <g transform="matrix(.013,0,0,-0.013,166.82,31.484)"> <use xlink:href="#g113-47"></use> </g> <g transform="matrix(.013,0,0,-0.013,171.96,31.484)"> <use xlink:href="#g113-47"></use> </g> <g transform="matrix(.013,0,0,-0.013,177.14,31.484)"> <use xlink:href="#g113-45"></use> </g> <g transform="matrix(.013,0,0,-0.013,182.28,31.484)"> <use xlink:href="#g113-118"></use> </g> <g transform="matrix(.013,0,0,-0.013,189.27,31.484)"> <use xlink:href="#g113-45"></use> </g> <g transform="matrix(.013,0,0,-0.013,194.42,31.484)"> <use xlink:href="#g113-115"></use> </g> <g transform="matrix(.013,0,0,-0.013,211.21,31.484)"> <path d="M-161 592L-215 609L-427 -83L-372 -100L-161 592Z" id="g117-145"></path> </g> <g transform="matrix(.013,0,0,-0.013,203.54,31.484)"> <use xlink:href="#g117-34"></use> </g> <g transform="matrix(.013,0,0,-0.013,214.83,31.484)"> <use xlink:href="#g113-114"></use> </g> <g transform="matrix(.013,0,0,-0.013,221.21,31.484)"> <path d="M273 -404V944H76V909L99 908C205 900 208 895 208 751V-249C208 -355 206 -360 99 -368L76 -369V-404H273Z" id="g119-130"></path> </g> <g transform="matrix(.013,0,0,-0.013,228.02,20.093)"> <use xlink:href="#g113-47"></use> </g> </g> </svg> <svg class="alt_equation" height="60.7063pt" id="I68" version="1.1" viewbox="0 0 243.89 60.7063" width="243.89pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <use transform="matrix(1 0 0 1 0 -10.91)" xlink:href="#B68-1"></use> <use transform="matrix(1 0 0 1 28.82 -10.91)" xlink:href="#B68-2"></use> <use transform="matrix(1 0 0 1 12.86 23.39)" xlink:href="#B68-3"></use> </svg></span></span><span class="right_break" id="R68"> <svg class="label" height="11.44pt" id="M68-4" version="1.1" viewbox="0 0 15.338 11.44" width="15.338pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B68-4"> <g transform="matrix(.013,0,0,-0.013,0,9.25)"> <use xlink:href="#g190-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,4.5,9.25)"> <path d="M247 635C117 635 41 518 41 422C41 317 114 239 220 239C239 239 256 244 278 255L348 290C315 139 207 37 63 13L67 -15C93 -15 155 -5 207 17C343 71 443 203 443 385C443 520 371 635 247 635ZM231 602C331 602 355 476 355 390C355 371 354 349 351 325C334 310 298 294 261 294C177 294 128 369 128 457C128 516 155 602 231 602Z" id="g190-193"></path> </g> <g transform="matrix(.013,0,0,-0.013,10.84,9.25)"> <use xlink:href="#g190-42"></use> </g> </g> </svg> <svg class="alt_label" height="60.7063pt" id="IL68" version="1.1" viewbox="0 0 15.4 60.7063" width="15.4pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <use transform="matrix(1 0 0 1 0 24.42)" xlink:href="#B68-4"></use> </svg></span></span></p> <p>在上述过程中,<我>n</我><sub><i>我</我></sub>和<我>n</我><sub><i>k</我></sub>被认为超过1。如果<我>n</我><sub><i>我</我></sub>= 0 (<我>n</我><sub><i>k</我></sub>= 0),<我>n</我><sub><i>k</我></sub>≥1 (<我>n</我><sub><i>我</我></sub>≥1),<svg height="14.0944pt" id="M69" style="vertical-align:-5.341061pt" version="1.1" viewbox="-0.0498162 -8.75334 25.2921 14.0944" width="25.2921pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.013,0,0,-0.013,7.644,0)"> <use xlink:href="#g190-84"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,13.858,3.132)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,18.945,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.81,5.233)"> <use xlink:href="#g176-108"></use> </g> </svg>设置为0,以反映之间的显著差异<我>d</我><sub><i>我</我></sub>和<我>d</我><sub><i>k</我></sub>。然而,如果<我>n</我><sub><i>我</我></sub>= 0和<我>n</我><sub><i>k</我></sub>= 0,即没有加密流<我>d</我><sub><i>我</我></sub>和<我>d</我><sub><i>k</我></sub>,<svg height="14.0944pt" id="M70" style="vertical-align:-5.341061pt" version="1.1" viewbox="-0.0498162 -8.75334 25.2921 14.0944" width="25.2921pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.013,0,0,-0.013,7.644,0)"> <use xlink:href="#g190-84"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,13.858,3.132)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,18.945,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.81,5.233)"> <use xlink:href="#g176-108"></use> </g> </svg>设置为1,因为他们表现出不同的行为,即。,他们不产生任何加密流量。</p> <p>同样,我们让<span class="inline_break"> <svg height="14.0944pt" id="M71" style="vertical-align:-5.341061pt" version="1.1" viewbox="-0.0498162 -8.75334 35.124 14.0944" width="35.124pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.013,0,0,-0.013,7.644,0)"> <use xlink:href="#g190-84"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,13.858,3.132)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,18.945,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.967,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,27.493,0)"> <use xlink:href="#g117-34"></use> </g> </svg><span class="irelop"></span> <svg height="14.0944pt" style="vertical-align:-5.341061pt" version="1.1" viewbox="38.7061838 -8.75334 6.392 14.0944" width="6.392pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,38.756,0)"> <use xlink:href="#g113-50"></use> </g> </svg></span>和这些相似度值表示为一个向量<span class="inline_break"> <svg height="17.1151pt" id="M72" style="vertical-align:-5.341001pt" version="1.1" viewbox="-0.0498162 -11.7741 49.737 17.1151" width="49.737pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-84"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,6.136,-5.741)"> <use xlink:href="#g50-106"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,6.071,3.784)"> <path d="M152 404V712C115 698 54 683 7 677V654C71 648 73 642 73 579V24C128 -2 179 -12 220 -12C353 -12 471 92 471 238C471 357 381 449 274 449C262 449 249 446 233 439L152 404ZM152 374C170 384 202 393 230 393C313 393 382 326 382 213C382 97 330 26 246 26C194 26 165 62 158 81C154 91 152 101 152 116V374Z" id="g190-99"></path> </g> <g transform="matrix(.0091,0,0,-0.0091,10.776,3.784)"> <use xlink:href="#g190-102"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,14.607,3.784)"> <use xlink:href="#g190-105"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,19.439,3.784)"> <path d="M433 39L423 65C413 59 399 54 387 54C370 54 352 69 352 114V299C352 352 342 392 307 422C285 440 255 449 225 449C168 437 102 399 75 379C56 365 44 353 44 339C44 315 69 296 87 296C101 296 111 303 116 319C124 349 133 371 145 385C156 397 171 404 190 404C241 404 275 364 275 291V274C253 256 180 229 120 209C65 190 39 159 39 110C39 47 88 -12 159 -12C189 -12 237 25 277 52C282 35 288 21 301 8C312 -3 333 -12 348 -12L433 39ZM275 84C256 65 221 48 195 48C164 48 124 73 124 124C124 161 146 180 185 198C206 208 254 229 275 240V84Z" id="g190-98"></path> </g> <g transform="matrix(.0091,0,0,-0.0091,23.269,3.784)"> <path d="M478 437H300V411C357 404 363 393 347 345C325 280 293 190 258 107C229 178 188 284 163 354C147 397 149 405 203 411V437H-2V411C52 403 59 396 82 339C130 222 176 109 220 -11H248C304 138 356 261 390 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<use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,76.825,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,78.69,5.233)"> <use xlink:href="#g176-50"></use> </g> <g transform="matrix(.013,0,0,-0.013,82.936,0)"> <use xlink:href="#g113-45"></use> </g> </svg><span class="ipunc"></span> <svg height="17.1151pt" style="vertical-align:-5.341001pt" version="1.1" viewbox="88.0291838 -11.7741 28.019 17.1151" width="28.019pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,88.079,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.013,0,0,-0.013,95.723,0)"> <use xlink:href="#g190-84"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,101.937,3.132)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,107.023,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,108.889,5.233)"> <use xlink:href="#g176-51"></use> </g> <g transform="matrix(.013,0,0,-0.013,113.134,0)"> <use xlink:href="#g113-45"></use> </g> </svg><span class="ipunc"></span> <svg height="17.1151pt" style="vertical-align:-5.341001pt" version="1.1" viewbox="118.2271838 -11.7741 18.427 17.1151" width="18.427pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,118.277,0)"> <use xlink:href="#g113-47"></use> </g> <g transform="matrix(.013,0,0,-0.013,123.421,0)"> <use xlink:href="#g113-47"></use> </g> <g transform="matrix(.013,0,0,-0.013,128.564,0)"> <use xlink:href="#g113-47"></use> </g> <g transform="matrix(.013,0,0,-0.013,133.74,0)"> <use xlink:href="#g113-45"></use> </g> </svg><span class="ipunc"></span><span class="nowrap"> <svg height="17.1151pt" style="vertical-align:-5.341001pt" version="1.1" viewbox="138.8331838 -11.7741 30.255 17.1151" width="30.255pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,138.883,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.013,0,0,-0.013,146.527,0)"> <use xlink:href="#g190-84"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,152.741,3.132)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,157.828,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,159.693,5.233)"> <path d="M541 97L524 132C497 101 450 73 440 73C435 73 433 81 438 112C459 231 485 344 513 454H504L425 426C395 291 413 366 391 279C348 194 231 66 163 66C154 66 139 82 152 137L206 371C221 437 216 454 185 454C160 454 97 423 25 355L38 321C85 359 111 379 120 379S127 369 121 341L67 113C61 89 60 69 60 53C60 3 82 -12 110 -12C135 -12 168 -5 200 19C253 58 315 106 371 181H373L359 111C337 -1 359 -12 378 -12C417 -12 480 31 541 97Z" id="g176-118"></path> </g> <g transform="matrix(.013,0,0,-0.013,164.408,0)"> <use xlink:href="#g113-126"></use> </g> </svg>。</span></span></p> <h5 id="sec5.5">5.5。聚类相似度值和恶意软件检测</h5> <p>从交通内容相似<svg height="14.0944pt" id="M73" style="vertical-align:-5.341061pt" version="1.1" viewbox="-0.0498162 -8.75334 26.2969 14.0944" width="26.2969pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-68"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.645,0)"> <use xlink:href="#g190-84"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,14.862,3.132)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,19.949,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,21.815,5.233)"> <use xlink:href="#g176-108"></use> </g> </svg>和交通行为相似<span class="nowrap"> <svg height="14.0944pt" id="M74" style="vertical-align:-5.341061pt" version="1.1" viewbox="-0.0498162 -8.75334 25.2921 14.0944" width="25.2921pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.013,0,0,-0.013,7.644,0)"> <use xlink:href="#g190-84"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,13.858,3.132)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,18.945,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.81,5.233)"> <use xlink:href="#g176-108"></use> </g> </svg>,</span>我们可以确定最终的相似度值<svg height="14.0944pt" id="M75" style="vertical-align:-5.341061pt" version="1.1" viewbox="-0.0498162 -8.75334 25.2921 14.0944" width="25.2921pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.013,0,0,-0.013,7.644,0)"> <use xlink:href="#g190-84"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,13.858,3.132)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,18.945,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.81,5.233)"> <use xlink:href="#g176-108"></use> </g> </svg>之间的特性集<我>d</我><sub><i>我</我></sub>和<我>d</我><sub><i>k</我></sub>用方程表示(<a href="#EEq10">10</a>)。在这个方程,<我>问</我>是重量值。在我们的实验中,我们设置<我>问</我>= 0.5,即交通内容相似度和交通行为相似性被分配相同的重量。这是因为应用程序通常产生几乎相同数量的HTTP和HTTPS流(<a href="#B57">57</a>]。我们也评估各种加权值的部分<a href="#sec6.2">6.2</a>,实验结果支持,0.5是最合适的值。的特性集<我>d</我><sub><i>我</我></sub>,一个向量<span class="inline_break"> <svg height="14.6294pt" id="M76" style="vertical-align:-5.34107pt" version="1.1" viewbox="-0.0498162 -9.28833 25.309 14.6294" width="25.309pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-84"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,6.071,3.132)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,11.158,5.233)"> <use 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style="vertical-align:-5.34107pt" version="1.1" viewbox="55.8001838 -9.28833 20.233 14.6294" width="20.233pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,55.85,0)"> <use xlink:href="#g113-84"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,61.921,3.132)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,67.008,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,68.874,5.233)"> <use xlink:href="#g176-51"></use> </g> <g transform="matrix(.013,0,0,-0.013,73.119,0)"> <use xlink:href="#g113-45"></use> </g> </svg><span class="ipunc"></span> <svg height="14.6294pt" style="vertical-align:-5.34107pt" version="1.1" viewbox="78.2121838 -9.28833 18.427 14.6294" width="18.427pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,78.262,0)"> <use xlink:href="#g113-47"></use> </g> <g 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</svg></span>终于获得,其中包含之间相似性值吗<我>d</我><sub><i>我</我></sub>和其他特性集。向量的集合<span class="inline_break"> <svg height="14.6294pt" id="M77" style="vertical-align:-5.34107pt" version="1.1" viewbox="-0.0498162 -9.28833 26.032 14.6294" width="26.032pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-124"></use> </g> <g transform="matrix(.013,0,0,-0.013,4.511,0)"> <use xlink:href="#g113-84"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,10.582,3.132)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,15.669,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.013,0,0,-0.013,18.557,0)"> <use xlink:href="#g113-126"></use> </g> <g transform="matrix(.013,0,0,-0.013,23.068,0)"> <use xlink:href="#g113-45"></use> </g> </svg><span class="ipunc"></span> <svg height="14.6294pt" style="vertical-align:-5.34107pt" version="1.1" viewbox="28.1611838 -9.28833 14.812 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xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B78-2"> <g transform="matrix(.013,0,0,-0.013,0,9.25)"> <use xlink:href="#g190-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,4.49,9.25)"> <use xlink:href="#g190-213"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.82,9.25)"> <path d="M248 635C97 635 43 457 43 311C43 153 97 -12 247 -12S450 166 450 312C450 466 397 635 248 635ZM246 603C337 603 361 452 361 312S337 20 248 20S132 172 132 313C132 452 156 603 246 603Z" id="g190-254"></path> </g> <g transform="matrix(.013,0,0,-0.013,15.23,9.25)"> <use xlink:href="#g190-42"></use> </g> </g> </svg> <svg class="alt_label" height="15.9342pt" id="IL78" version="1.1" viewbox="0 0 19.8 15.9342" width="19.8pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <use transform="matrix(1 0 0 1 0 2.04)" xlink:href="#B78-2"></use> </svg></span></span></p> <p>具体而言,我们使用峰值密度聚类方法(<a href="#B58">58</a>实现我们的目标。密度峰聚类是基于以下假设:集群中心的特点是密度高于他们的邻居和一个相对大点的距离有更高的密度。因此,密度峰值集群可以自动识别正确的数量的集群。这是很重要的,因为我们不知道是否有重新包装恶意软件或有多少类型的恶意软件重新包装。换句话说,我们不能提前确定集群的数量。密度峰值集群可以帮助我们克服这一挑战。</p> <p>我们假设大多数移动设备已经安装了原始的应用程序,作为讨论的部分<a href="#sec5.1">5.1</a>。因此,聚类后,最多的体素的集群将被认为是原始的,和其余集群将被视为可疑。然而,可疑程序不一定是重新包装的恶意软件。例如,应用程序只能重新包装展示广告。这种类型的打包应用程序不应该简单地判断恶意软件。此外,原始应用程序可以怀疑由于不同的用户行为。为了进一步减少假警报的频率,我们可以检查服务器主机名使用VirusTotal重新包装中包含集群(url包含在HTTP流量内容)。如果所有的可疑的集群服务器的主机名<我>C</我><sub><i>r</我></sub>判断是干净的,它将被视为一个集群的异常但是无害的应用。否则,它将确定为重新包装的恶意软件。通过这种方法,我们可以准确地检测重新包装Android恶意软件。在这一步中,我们只使用VirusTotal白名单排除假警报。我们不使用它作为重版书(检测签名)来检测恶意软件重新包装。恶意软件检测仍实现了聚类相似度值。</p> <h4 id="evaluation">6。评价</h4> <h5 id="sec6.1">6.1。系统实现和数据集</h5> <p>图<a href="//www.newsama.com/journals/scn/2020/8630748/fig11/" target="_blank">11</a>说明我们的实验设置。安卓手机通过无线连接到边缘服务器,每个电话都有安装edge-client应用,将流的元发送到边缘服务器使用套接字(java.net.Socket)。边缘是一个戴尔PowerEdge R730服务器(32处理器、16 GB的RAM和12 TB的硬盘)配置作为一个访问点。在边缘服务器,我们使用<我>tcpdump</我>(<a href="http://www.tcpdump.org/" target="_blank">http://www.tcpdump.org/</a>)收集网络流量。交通内容和行为的相似性计算和聚类的相似性值是在Windows Azure云计算平台上实现。使用URL进行检查<我>Virustotal</我>(<a href="http://www.virustotal.com/" target="_blank">https://www.virustotal.com/</a>)。</p> <div class="floats-partial-section partial-carousel-wrapper" data-section="fig11"> <div class="floats-partial-content fig-content-fig11"> <div class="partial-carousel--single-image"> <img alt="" name="8630748.fig.0011" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.0011.svgz"> <br> <strong></strong> </div> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">图11</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/fig11/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 实验设置。</d我v> </div> </div> <p>在实现中,我们使用<我>aria2c</我>(<a href="https://aria2.github.io/" target="_blank">https://aria2.github.io/</a>)从Androzoo下载应用程序(<a href="https://androzoo.uni.lu/" target="_blank">https://androzoo.uni.lu/</a>)。aria2c在Python代码封装为命令并行下载。下载应用程序后,我们自动安装手机使用<我>亚洲开发银行</我>shell命令。每个手机都有40测试应用程序安装。我们已经实现了edge-client应用基于Android的VPN服务。在我们的实现中,edge-client应用网络流和相关应用,解决港口和pid(进程id)将收集到的新流的元发送到边缘服务器每隔60秒。使用的边缘服务器<我>tcpdump</我>收集网络流量,保存为pcap文件。提取交通特性,我们使用<我>Splitcap</我>(<a href="http://www.netresec.com/?page=SplitCap" target="_blank">https://www.netresec.com/?page=SplitCap</a>从pcap文件)恢复tcp流。然后,HTTP流量,我们提取内容使用tshark (<a href="http://www.wireshark.org/docs/man-pages/tshark.html" target="_blank">https://www.wireshark.org/docs/man-pages/tshark.html</a>)命令<我>- z遵循</我>,<我>tcp</我>,<我>美国信息交换标准代码</我>。包的大小和包间隔时间也得到tshark——与命令<我>e frame.len</我>- - - - - -<我>e frame.time_relative</我>。在云中,<svg height="14.0944pt" id="M79" style="vertical-align:-5.341061pt" version="1.1" viewbox="-0.0498162 -8.75334 26.2969 14.0944" width="26.2969pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-68"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.645,0)"> <use xlink:href="#g190-84"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,14.862,3.132)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,19.949,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,21.815,5.233)"> <use xlink:href="#g176-108"></use> </g> </svg>和<svg height="14.0944pt" id="M80" style="vertical-align:-5.341061pt" version="1.1" viewbox="-0.0498162 -8.75334 25.2921 14.0944" width="25.2921pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g190-67"></use> </g> <g transform="matrix(.013,0,0,-0.013,7.644,0)"> <use xlink:href="#g190-84"></use> </g> <g transform="matrix(.0091,0,0,-0.0091,13.858,3.132)"> <use xlink:href="#g50-101"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,18.945,5.233)"> <use xlink:href="#g176-106"></use> </g> <g transform="matrix(.0065,0,0,-0.0065,20.81,5.233)"> <use xlink:href="#g176-108"></use> </g> </svg>计算使用scikit-learn (<a href="http://scikit-learn.org/" target="_blank">http://scikit-learn.org/</a>)和Numpy (<a href="https://plot.ly/numpy/norm/" target="_blank">https://plot.ly/numpy/norm/</a>)。的代码密度峰值集群可以在GitHub (<a href="https://github.com/jasonwbw/DensityPeakCluster" target="_blank">https://github.com/jasonwbw/DensityPeakCluster</a>),我们有固定的各种错误出现在原始代码。</p> <p>我们已经下载了200对原始和打包的应用程序从Androzoo进行测试。然而,并不是所有这些重新打包应用程序恶意下载。一些应用程序只有重新包装显示额外的广告。筛选出Android恶意软件的下载打包应用程序,我们进一步检查了200个使用Virustotal重新打包应用程序。如果一个应用程序被认为是安全的所有的杀毒工具,贴上<我>repackaged_safe</我>在我们的实验。否则,它被贴上<我>repackaged_malware</我>。总的来说,通过Virustotal 143重新打包应用程序检测恶意软件。然而,在我们的实验中,我们评估了聚类方法在所有200年提出重新打包应用程序获得更实际的性能结果。</p> <p>下载的应用程序运行在10的Android手机并行加速实验进程。对所有应用程序中,我们使用Droidbot [<a href="#B59">59</a>)输入事件发送给他们,自动生成网络流量。我们每个重新打包应用程序(repackaged_safe和repackaged_malware应用)和相应的原始应用程序30倍十倍以产生足够的网络流量。原始应用程序的运行时间超过了重新打包的应用程序,因为我们假设大多数的应用程序是原始的,作为讨论的部分<a href="#sec5.1">5.1</a>。因此,我们获得40流量为每一对repackaged-original程序集。注意,从移动设备和边缘服务器,只有200个不同的应用程序,因为重新打包应用程序具有相同的名称作为相应的原始应用。因此,我们的实验模拟200 = 8000∗移动设备。对于每一对repackaged-original应用来说,有30设备与原程序和10设备重新打包的版本。</p> <p>总的来说,我们收集到的近89 GB网络流量。的数据集用于我们的实验总结在表<a href="//www.newsama.com/journals/scn/2020/8630748/tab3/" target="_blank">3</a>。表中,交通数据集的大小是捕获网络流量的大小,和特征数据集大小的尺寸提取的特征。在我们的实验中,HTTP流量内容和流量统计功能,如表所示<a href="//www.newsama.com/journals/scn/2020/8630748/tab2/" target="_blank">2</a>都保存为文本文件。如表所示<a href="//www.newsama.com/journals/scn/2020/8630748/tab3/" target="_blank">3</a>,特征数据集明显小于流量数据集(25 g vs 63 g和9 g vs 26 g)。因此,边缘计算可以减少数据量,提高数据采集速度云计算(<a href="#B24">24</a>]。因为特征数据集大小仍大(25 g + 9 g),我们没有同时发送所有这些特性数据到云。相反,我们发送特性数据。当一个应用程序的特性数据被成功接收到云,其交通相似性计算和集群。之后,另一个应用程序的特性数据将发送和分析。实验结果将在下面。</p> <div class="floats-partial-section partial-other-wrapper" data-section="tab3"> <div class="floats-partial-content fig-content-tab3"> <table class="table-group" id="tab3"> <tbody> <tr> <td> <table class="table"> <tbody> <tr> <td class="thead-hr" colspan="7"> <hr></td> </tr> <tr class="thead"> <td class="align_left"></td> <td class="align_center">#的应用</td> <td class="align_center">#的运行</td> <td class="align_center">#的HTTP流</td> <td class="align_center">#加密流</td> <td class="align_center">交通数据集大小</td> <td class="align_center">特征数据集大小</td> </tr> <tr> <td class="thead-hr" colspan="7"> <hr></td> </tr> <tr> <td class="align_left">原始应用程序</td> <td class="align_center">200年</td> <td class="align_center">30.</td> <td class="align_center">340015年</td> <td class="align_center">183452年</td> <td class="align_center"><i>≈</我>63 G字节</td> <td class="align_center"><i>≈</我>25 G字节</td> </tr> <tr> <td class="align_left">重新打包应用程序</td> <td class="align_center">200年</td> <td class="align_center">10</td> <td class="align_center">110670年</td> <td class="align_center">93041年</td> <td class="align_center"><i>≈</我>26 G字节</td> <td class="align_center"><i>≈</我>9 G字节</td> </tr> <tr class="table-tr"> <td colspan="7"> <hr class="tbody-hr"></td> </tr> </tbody> </table></td> </tr> </tbody> </table> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">表3</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/tab3/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 实验中使用的数据集。</d我v> </div> </div> <h5 id="sec6.2">6.2。实验结果</h5> <p>在本节中,我们主要由聚类评估Android恶意软件的检测效率相似度值。的绩效评估方法的权力,内存和CPU消耗在以下部分阐述<a href="#sec6.3">6.3</a>。</p> <p>类似于以前的研究(<a href="#B8">8</a>,<a href="#B14">14</a>),测量方法的性能,精度和<我>F -</我>利用测量指标,定义在方程(<a href="#EEq11">11</a>)和(<a href="#EEq11">12</a>)。在方程(<a href="#EEq11">11</a>)、TP、FN、FP和TN在表中定义<a href="//www.newsama.com/journals/scn/2020/8630748/tab4/" target="_blank">4</a>。在表<a href="//www.newsama.com/journals/scn/2020/8630748/tab4/" target="_blank">4</a>,<我>repackaged_x</我>代表<我>repackaged_safe</我>或<我>repackaged_malware</我>。方程的精度和召回(<a href="#EEq11">12</a>)通过方程计算(<a href="#EEq11">13</a>)和(<a href="#EEq11">14</a>):<span class="equation_break" id="EEq11"><span class="left_break" id="L81"></span><span class="middle_break"><span class="center_break" id="M81"> <svg height="137.541pt" id="M81-1" version="1.1" viewbox="0 0 48.847 137.541" width="48.847pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B81-1"> <g transform="matrix(.013,0,0,-0.013,0,17.261)"> <path d="M673 0V28C608 34 594 43 563 129C499 303 432 494 370 665L339 656L132 132C98 43 84 37 20 28V0H238V28C162 35 154 45 175 108C188 150 203 192 219 237H432C454 176 474 122 487 83S491 36 428 28V0H673ZM418 280H234C265 362 296 450 328 535H330L418 280Z" id="g190-66"></path> </g> <g transform="matrix(.013,0,0,-0.013,8.65,17.261)"> <use xlink:href="#g190-100"></use> </g> <g 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xmlns:xlink="http://www.w3.org/1999/xlink"> <g id="B81-10"> <g transform="matrix(.013,0,0,-0.013,0,9.26)"> <use xlink:href="#g190-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,4.5,9.26)"> <use xlink:href="#g190-213"></use> </g> <g transform="matrix(.013,0,0,-0.013,8.68,9.26)"> <use xlink:href="#g190-166"></use> </g> <g transform="matrix(.013,0,0,-0.013,15.14,9.26)"> <use xlink:href="#g190-42"></use> </g> </g> </svg></span></span></p> <div class="floats-partial-section partial-other-wrapper" data-section="tab4"> <div class="floats-partial-content fig-content-tab4"> <table class="table-group" id="tab4"> <tbody> <tr> <td> <table class="table"> <tbody> <tr> <td class="thead-hr" colspan="3"> <hr></td> </tr> <tr class="thead"> <td class="align_left" rowspan="2">观察到的</td> <td class="align_center" colspan="2">检测到</td> </tr> <tr class="thead"> <td class="align_center">Repackaged_x应用</td> <td class="align_center">原始应用程序</td> </tr> <tr> <td class="thead-hr" colspan="3"> <hr></td> </tr> <tr> <td class="align_left">Repackaged_x应用</td> <td class="align_center">TPs的TP (#)</td> <td class="align_center">FN FN (#)</td> </tr> <tr> <td class="align_left">原始应用程序</td> <td class="align_center">FP FPs (#)</td> <td class="align_center">TNs的TN (#)</td> </tr> <tr class="table-tr"> <td colspan="3"> <hr class="tbody-hr"></td> </tr> </tbody> </table></td> </tr> </tbody> </table> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">表4</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/tab4/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 混淆矩阵。</d我v> </div> </div> <p>我们已经评估的准确性和<我>F -</我>测量每个包装应用。记得我们每个重新打包应用程序和相应的原始应用程序30倍十倍。为每个应用程序,因此,最初的应用流量的数量设置为30,和打包的应用程序流量的数量是10,即TP + FN = 10和TN + FP = 30为每个应用程序。我们从repackage_malware随机选择20应用,和实验结果对这些应用程序介绍了数字<a href="//www.newsama.com/journals/scn/2020/8630748/fig12/" target="_blank">12</a>和<a href="//www.newsama.com/journals/scn/2020/8630748/fig13/" target="_blank">13</a>。选择20列出应用程序的详细描述表<a href="//www.newsama.com/journals/scn/2020/8630748/tab5/" target="_blank">5</a>。在表中,每个应用程序的主要功能是由分析AndroidManifest的包名。xml和Google搜索结果的包名称。如图<a href="//www.newsama.com/journals/scn/2020/8630748/fig12/" target="_blank">12</a>实现100%的准确率,总共6应用程序(app3, app5 app9, app10, app13,和app18)。最小精度是85% (app2, 34/40),平均精度为95.2%。图<a href="//www.newsama.com/journals/scn/2020/8630748/fig13/" target="_blank">13</a>介绍了<我>F -</我>测量值。在我们的实验中,最大值<我>F -</我>测量值是1,最小值是0.737。平均<我>F -</我>测量值是0.888。这些结果表明我们提出的聚类方法的令人满意的性能。</p> <div class="floats-partial-section partial-carousel-wrapper" data-section="fig12"> <div class="floats-partial-content fig-content-fig12"> <div class="partial-carousel--single-image"> <img alt="" name="8630748.fig.0012" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.0012.svgz"> <br> <strong></strong> </div> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">图12</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/fig12/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 检测精度为20选定的应用程序。</d我v> </div> </div> <div class="floats-partial-section partial-carousel-wrapper" data-section="fig13"> <div class="floats-partial-content fig-content-fig13"> <div class="partial-carousel--single-image"> <img alt="" name="8630748.fig.0013" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.0013.svgz"> <br> <strong></strong> </div> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">图13</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/fig13/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 检测<我>F</我>测量20所选应用程序。</d我v> </div> </div> <div class="floats-partial-section partial-other-wrapper" data-section="tab5"> <div class="floats-partial-content fig-content-tab5"> <table class="table-group" id="tab5"> <tbody> <tr> <td> <table class="table"> <tbody> <tr> <td class="thead-hr" colspan="4"> <hr></td> </tr> <tr class="thead"> <td class="align_left"></td> <td class="align_center">应用程序的主要功能</td> <td class="align_center">#的HTTP流</td> <td class="align_center">#加密流</td> </tr> <tr> <td class="thead-hr" colspan="4"> <hr></td> </tr> <tr> <td class="align_left">App1</td> <td class="align_center">放像机</td> <td class="align_center">453年</td> <td class="align_center">51</td> </tr> <tr> <td class="align_left">App2</td> <td class="align_center">游戏</td> <td class="align_center">657年</td> <td class="align_center">1455年</td> </tr> <tr> <td class="align_left">App3</td> <td class="align_center">浏览器</td> <td class="align_center">1531年</td> <td class="align_center">1478年</td> </tr> <tr> <td class="align_left">App4</td> <td class="align_center">MusicPlayer</td> <td class="align_center">341年</td> <td class="align_center">25</td> </tr> <tr> <td class="align_left">App5</td> <td class="align_center">游戏</td> <td class="align_center">612年</td> <td class="align_center">289年</td> </tr> <tr> <td class="align_left">App6</td> <td class="align_center">游戏</td> <td class="align_center">788年</td> <td class="align_center">123年</td> </tr> <tr> <td class="align_left">App7</td> <td class="align_center">游戏</td> <td class="align_center">1336年</td> <td class="align_center">524年</td> </tr> <tr> <td class="align_left">App8</td> <td class="align_center">健身</td> <td class="align_center">357年</td> <td class="align_center">892年</td> </tr> <tr> <td class="align_left">App9</td> <td class="align_center">电子邮件</td> <td class="align_center">122年</td> <td class="align_center">431年</td> </tr> <tr> <td class="align_left">App10</td> <td class="align_center">游戏</td> <td class="align_center">963年</td> <td class="align_center">790年</td> </tr> <tr> <td class="align_left">App11</td> <td class="align_center">MusicPlayer</td> <td class="align_center">1128年</td> <td class="align_center">547年</td> </tr> <tr> <td class="align_left">App12</td> <td class="align_center">游戏</td> <td class="align_center">1598年</td> <td class="align_center">426年</td> </tr> <tr> <td class="align_left">App13</td> <td class="align_center">新闻</td> <td class="align_center">2460年</td> <td class="align_center">1178年</td> </tr> <tr> <td class="align_left">App14</td> <td class="align_center">新闻</td> <td class="align_center">2891年</td> <td class="align_center">1543年</td> </tr> <tr> <td class="align_left">App15</td> <td class="align_center">聊天</td> <td class="align_center">171年</td> <td class="align_center">49</td> </tr> <tr> <td class="align_left">App16</td> <td class="align_center">电子邮件</td> <td class="align_center">143年</td> <td class="align_center">368年</td> </tr> <tr> <td class="align_left">App17</td> <td class="align_center">天气预报</td> <td class="align_center">397年</td> <td class="align_center">120年</td> </tr> <tr> <td class="align_left">App18</td> <td class="align_center">游戏</td> <td class="align_center">1832年</td> <td class="align_center">921年</td> </tr> <tr> <td class="align_left">App19</td> <td class="align_center">健身</td> <td class="align_center">732年</td> <td class="align_center">362年</td> </tr> <tr> <td class="align_left">App20</td> <td class="align_center">OnlineLearning</td> <td class="align_center">2378年</td> <td class="align_center">834年</td> </tr> <tr class="table-tr"> <td colspan="4"> <hr class="tbody-hr"></td> </tr> </tbody> </table></td> </tr> </tbody> </table> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">表5</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/tab5/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 详细描述的选择20个应用程序。</d我v> </div> </div> <p>我们也计算了平均精度和<我>F</我>所有repackaged_safe测量值和repackaged_malware应用。在这些计算,TP + FN = 57∗10 = 570和TN + FP = 57∗30 = 1710 repackaged_safe应用。repackaged_malware应用,TP + FN = 143∗10 = 1430和TN + FP = 143∗30 = 4290。这是因为在我们的实验中,143个应用程序被认定为恶意软件打包,57应用作为Virustotal重新包装安全。因此,参数值不同。实验结果表中列出<a href="//www.newsama.com/journals/scn/2020/8630748/tab6/" target="_blank">6</a>。</p> <div class="floats-partial-section partial-other-wrapper" data-section="tab6"> <div class="floats-partial-content fig-content-tab6"> <table class="table-group" id="tab6"> <tbody> <tr> <td> <table class="table"> <tbody> <tr> <td class="thead-hr" colspan="3"> <hr></td> </tr> <tr class="thead"> <td class="align_left"></td> <td class="align_center">平均精度(%)</td> <td class="align_center">平均<我>F</我>测量</td> </tr> <tr> <td class="thead-hr" colspan="3"> <hr></td> </tr> <tr> <td class="align_left">Repackaged_safe</td> <td class="align_center">90.3</td> <td class="align_center">0.78</td> </tr> <tr> <td class="align_left">Repackaged_malware</td> <td class="align_center">96.9</td> <td class="align_center">0.94</td> </tr> <tr class="table-tr"> <td colspan="3"> <hr class="tbody-hr"></td> </tr> </tbody> </table></td> </tr> </tbody> </table> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">表6</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/tab6/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 平均的准确性和<我>F</我>测量。</d我v> </div> </div> <p>根据表<a href="//www.newsama.com/journals/scn/2020/8630748/tab6/" target="_blank">6</a>repackaged_safe和repackaged_malware应用,平均精度值都高。然而,平均<我>F</我>测量repackaged_safe应用只有0.78,低于重新包装的恶意软件。这表明重新包装安全应用程序很难区分原来的应用程序。这是因为repackaged_safe应用只产生少量的额外的网络流,和他们的网络流量特征不清晰可辨的正常交通。幸运的是,平均<我>F</我>测量重新打包的恶意软件程序是杰出的。这可能是由于这一事实恶意软件通常发送被盗数据或从远程服务器接收命令。因此,他们的特殊网络流量特性和区分。图<a href="//www.newsama.com/journals/scn/2020/8630748/fig14/" target="_blank">14</a>礼物的一个示例应用程序集群和说明了重新包装的分辨率恶意软件和原始应用程序。这些结果说明重新包装Android恶意软件可以有效地检测到通过比较他们的网络流量与原始应用程序。</p> <div class="floats-partial-section partial-carousel-wrapper" data-section="fig14"> <div class="floats-partial-content fig-content-fig14"> <div class="partial-carousel--single-image"> <img alt="" name="8630748.fig.0014" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.0014.svgz"> <br> <strong></strong> </div> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">图14</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/fig14/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 应用聚类的例子。很明显,两个集群。左上角的点是一个异类。检测到异常值异常但无害的应用方法。这个数字是由峰值密度聚类工具。</d我v> </div> </div> <p>重新包装的恶意软件应用,精度结果与不同重量值(<我>问</我>在方程(<a href="#EEq10">10</a>呈现在图<a href="//www.newsama.com/journals/scn/2020/8630748/fig15/" target="_blank">15</a>。图中描绘的<我>问</我>= 0.5,我们意识到准确率最高,为96.9%。如果<我>问</我>= 0,即只使用加密流量的特点,准确的结果是75.3%。结果是61.7%<我>问</我>= 1,即只考虑明文传输的特点。这些结果说明加密和明文交通导致分化的原始应用程序和重新包装的恶意软件。然而,交通贡献超过明文加密流量。这可能因为恶意程序通常连接到他们的服务器的安全协议来规避IDS检测。</p> <div class="floats-partial-section partial-carousel-wrapper" data-section="fig15"> <div class="floats-partial-content fig-content-fig15"> <div class="partial-carousel--single-image"> <img alt="" name="8630748.fig.0015" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.0015.svgz"> <br> <strong></strong> </div> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">图15</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/fig15/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 精度的各种重量值交通内容相似度和交通行为的相似性。</d我v> </div> </div> <p>在前面的实验中,我们检查了服务器的主机名使用VirusTotal减少假阳性的频率。为各种集群包含少于20元素,如果所有的服务器的主机名的人被认为是清洁,集群被确认为一个原始应用程序而不是重新包装。认为在节<a href="#sec5.5">5.5</a>,这个过程只减少了假警报的频率。支持这个论点,我们列出真阳性和假阳性的数量143重新包装的恶意软件在表<a href="//www.newsama.com/journals/scn/2020/8630748/tab7/" target="_blank">7</a>进行比较。进行主机名时检查,真阳性的数量是1400,结果都是一样的,当主机名检查是关闭的。这个发现支持,恶意软件检测到聚类相似度值。然而,假阳性的数量从47岁增加到213年的主机名检查。因此,我们建议检查服务器的主机名后集群提高该方法的实用性。注意,假阳性VirusTotal仍然发生在当我们检查主机名。因此,可能存在恶意软件在最初的应用程序。在我们的数据集,典型的例子<我>com.mobo.video.player.pro</我>和<我>cn.cf。商店ele1.taoxiaosan</我>。我们进一步分析这两个应用程序通过阅读他们的反编译代码,我们确定他们确实与可疑的服务器建立连接。在细节,在不同的运行时,应用程序<我>com.mobo.video.player.pro</我>与<a href="http://www.topappsquare.com/" target="_blank">http://www.topappsquare.com,</a>恶意的判断是哪一个<我>CyRadar</我>在VirusTotal。应用程序<我>cn.cf。商店ele1.taoxiaosan</我>访问可疑网址<a href="http://955.cc/jSn9" target="_blank">http://955.cc/jSn9。</a>因为这些应用程序是原始的应用程序,他们被确定为假阳性的实验。</p> <div class="floats-partial-section partial-other-wrapper" data-section="tab7"> <div class="floats-partial-content fig-content-tab7"> <table class="table-group" id="tab7"> <tbody> <tr> <td> <table class="table"> <tbody> <tr> <td class="thead-hr" colspan="3"> <hr></td> </tr> <tr class="thead"> <td class="align_left"></td> <td class="align_center">#真正的阳性</td> <td class="align_center">#的假阳性</td> </tr> <tr> <td class="thead-hr" colspan="3"> <hr></td> </tr> <tr> <td class="align_left">与主机名检查</td> <td class="align_center">1400年</td> <td class="align_center">47</td> </tr> <tr> <td class="align_left">没有检查主机名</td> <td class="align_center">1400年</td> <td class="align_center">213年</td> </tr> <tr class="table-tr"> <td colspan="3"> <hr class="tbody-hr"></td> </tr> </tbody> </table></td> </tr> </tbody> </table> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">表7</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/tab7/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 和不使用主机名真阳性和假阳性检查。</d我v> </div> </div> <p>在我们的实验中,我们选择密度峰聚类的聚类方法,因为密度峰集群可以自动确定正确的数量的集群(<a href="#B58">58</a>]。因此,我们的方法可以检测各种版本的恶意软件从相同的原始应用程序重新打包。不幸的是,在从AndroZoo下载的应用程序,没有恶意软件从相同的原始应用程序重新打包。评估版本的恶意软件检测的有效性,我们创建了两个恶意软件实例从一个流行的游戏应用程序,也就是说,<我>air.com.aceviral.motox</我>3所示。一个是由嫁接AnserverBot的源代码<我>air.com.aceviral.motox</我>3,另一种是通过添加代码创建窃取用户的联系人和短信和发送到远程服务器。同样,每一个恶意软件运行10次和原始的应用程序<我>air.com.aceviral.motox</我>3也运行10次验证。聚类的结果呈现在图<a href="//www.newsama.com/journals/scn/2020/8630748/fig16/" target="_blank">16</a>。显然,有三个集群。实验结果表明,的价值<我>F</我>测量每一个恶意软件是1。因此,我们的方法可以检测各种恶意软件从相同的原始应用程序重新打包。</p> <div class="floats-partial-section partial-carousel-wrapper" data-section="fig16"> <div class="floats-partial-content fig-content-fig16"> <div class="partial-carousel--single-image"> <img alt="" name="8630748.fig.0016" src="https://static-01.hindawi.com/articles/scn/volume-2020/8630748/figures/8630748.fig.0016.svgz"> <br> <strong></strong> </div> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">图16</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/fig16/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 聚类结果的各种恶意软件重新包装<我>air.com.aceviral.motox</我>3所示。中间的异常值检测到异常但无害的程序。这个数字是密度峰值产生的聚类工具。</d我v> </div> </div> <h5 id="sec6.3">6.3。比较</h5> <p>在本节中,我们将我们的方法和典型的方法是基于网络或云,如图<a href="//www.newsama.com/journals/scn/2020/8630748/fig5/" target="_blank">5</a>。比较指标检测的准确性,<我>F</我>测量,平均功率、CPU和内存消耗的移动设备。首先,我们比较该方法与AppFA [<a href="#B14">14</a>),这是完全在网络层实现的。由于AppFA还必须分析应用流量,我们直接使用交通集重新包装的恶意软件应用比较。AppFA测试时,我们删除标签信息中包含的组和混合交通网络流作为一个整体。然后,我们使用了签名匹配和限制<我>K</我>聚类算法则提出了(<a href="#B14">14</a>恢复应用程序会话,即每个流的标签。类似的应用程序中使用AppFA选择通过方法介绍(在谷歌玩<a href="#B14">14</a>),对于每一个恶意软件重新包装,10类似的应用程序被选为对等组。对等组应用程序被Droidbot生成网络流量运行一次。比较结果列在表中<a href="//www.newsama.com/journals/scn/2020/8630748/tab8/" target="_blank">8</a>。</p> <div class="floats-partial-section partial-other-wrapper" data-section="tab8"> <div class="floats-partial-content fig-content-tab8"> <table class="table-group" id="tab8"> <tbody> <tr> <td> <table class="table"> <tbody> <tr> <td class="thead-hr" colspan="3"> <hr></td> </tr> <tr class="thead"> <td class="align_left"></td> <td class="align_center">该方法</td> <td class="align_center">AppFA</td> </tr> <tr> <td class="thead-hr" colspan="3"> <hr></td> </tr> <tr> <td class="align_left">精度</td> <td class="align_center">96.9%</td> <td class="align_center">86.3%</td> </tr> <tr> <td class="align_left"><i>F</我>测量</td> <td class="align_center">0.94</td> <td class="align_center">0.75</td> </tr> <tr> <td class="align_left">平均能耗</td> <td class="align_center">1.2%</td> <td class="align_center">0</td> </tr> <tr> <td class="align_left">平均CPU消耗</td> <td class="align_center">0.6%</td> <td class="align_center">0</td> </tr> <tr> <td class="align_left">平均内存消耗</td> <td class="align_center">6.54 MB</td> <td class="align_center">0</td> </tr> <tr class="table-tr"> <td colspan="3"> <hr class="tbody-hr"></td> </tr> </tbody> </table></td> </tr> </tbody> </table> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">表8</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/tab8/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 该方法的比较与AppFA。</d我v> </div> </div> <p>自从AppFA不需要安装一些特殊应用在移动设备上,额外的权力,内存和CPU消耗都是0。然而,检测精度低得多(86.3%比96.9%)相比,该方法的,而在表<a href="//www.newsama.com/journals/scn/2020/8630748/tab8/" target="_blank">8</a>。在该方法中,我们使用edge-client应用记录流元;因此,网络流可以准确地标记。然而,在AppFA,通过交通流标签实现聚类,聚类精度不能100%。同时,AppFA比较应用程序的网络行为与他们类似的应用程序,这也是导致错误。在该方法中,我们直接比较与原来的应用程序重新打包的恶意软件,并提高检测精度。平均功率,该方法的CPU和内存消耗也低,可以接受的。</p> <p>在表<a href="//www.newsama.com/journals/scn/2020/8630748/tab8/" target="_blank">8</a>、电源、内存和CPU消耗我们edge-client应用的帮助下得到应用GT (<a href="https://github.com/Tencent/GT" target="_blank">https://github.com/Tencent/GT</a>)。GT是一个便携式工具,智能手机上运行的调试应用程序内部参数和代码耗时的统计数据。功率的平均值、内存和CPU消耗计算如下。与Droidbot在运行应用程序之前,我们开始edge-client应用GT。Droidbot时停止,我们记录能力,CPU和内存消耗。我们重复这个过程,直到所有应用程序(包括143年重新包装恶意软件应用程序和原来的版本)已经测试。通过这种方式,我们获得的平均功率,CPU和内存消耗edge-client应用。根据表<a href="//www.newsama.com/journals/scn/2020/8630748/tab8/" target="_blank">8</a>,edge-client应用是轻量级的,移动设备的性能影响最小。</p> <p>然后,我们比较该方法与SAMADroid [<a href="#B44">44</a>]。SAMADroid监视器Android系统调用和发送到一个集中的服务器呼吁Android恶意软件的检测。设备内置SAMADroid是一个典型的基于云的检测方法。我们已经实现了动态检测根据描述(<a href="#B44">44</a>]。详细的api调用的运行应用程序监视工具<我>敏感的API监控</我>(<a href="https://github.com/cyruliu/Sensitive-API-Monitor" target="_blank">https://github.com/cyruliu/Sensitive-API-Monitor</a>)。在(做<a href="#B44">44</a>),10个系统调用的频率值(brk开放,ioctl,读、写,sendto, sendmsg、recvfrom,和recvmsg)记录。这些记录的频率值被发送到Windows Azure的恶意软件检测。我们评估SAMADroid的动态检测性能143 repackaged_malware应用程序和原来的版本。评估的频率值的原始应用程序是用于创建正常模型,并重新包装的频率值恶意软件应用程序是用于测试。我们也使用这个软件GT记录的权力,SAMADroid内存和CPU消耗。请注意,我们的手机都是扎根,<我>Sensitive_API_Monitor</我>可以使用和GT。实验结果展示在表<a href="//www.newsama.com/journals/scn/2020/8630748/tab9/" target="_blank">9</a>。</p> <div class="floats-partial-section partial-other-wrapper" data-section="tab9"> <div class="floats-partial-content fig-content-tab9"> <table class="table-group" id="tab9"> <tbody> <tr> <td> <table class="table"> <tbody> <tr> <td class="thead-hr" colspan="3"> <hr></td> </tr> <tr class="thead"> <td class="align_left"></td> <td class="align_center">该方法</td> <td class="align_center">SAMADroid</td> </tr> <tr> <td class="thead-hr" colspan="3"> <hr></td> </tr> <tr> <td class="align_left">精度</td> <td class="align_center">96.9%</td> <td class="align_center">83.1%</td> </tr> <tr> <td class="align_left"><i>F</我>测量</td> <td class="align_center">0.940</td> <td class="align_center">0.793</td> </tr> <tr> <td class="align_left">平均能耗</td> <td class="align_center">1.2%</td> <td class="align_center">2.3%</td> </tr> <tr> <td class="align_left">平均CPU消耗</td> <td class="align_center">0.6%</td> <td class="align_center">0.8%</td> </tr> <tr> <td class="align_left">平均内存消耗</td> <td class="align_center">6.54 MB</td> <td class="align_center">7.73 MB</td> </tr> <tr class="table-tr"> <td colspan="3"> <hr class="tbody-hr"></td> </tr> </tbody> </table></td> </tr> </tbody> </table> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">表9</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/tab9/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 该方法的比较与SAMADroid。</d我v> </div> </div> <p>最后,我们比较我们的方法与Shabtai的方法(<a href="#B8">8</a>]。Shabtai的方法检测到Android恶意软件的移动设备,它只考虑应用程序的网络流量模式;HTTP流量内容不考虑。这给了我们一个机会来比较我们的方法与专门设计了加密流量的方法。我们实现了Shabtai # 2的方法和选择功能子集的检测功能。# 2特征子集包括Avg。发送字节,Avg,收到过。字节,Pct. Avg。接到。字节,其他值,它被证实是恶意软件检测的最佳特征子集(<a href="#B8">8</a>]。决定选择/回归树分类算法。生成的测试数据集交通143年重新包装恶意软件实例,和训练集的交通是由相应的原始应用程序生成。分类结果列在表中<a href="//www.newsama.com/journals/scn/2020/8630748/tab10/" target="_blank">10</a>。根据表,检测准确性和<我>F</我>我们方法的测量值明显高于Shabtai的方法。这意味着HTTP流量为Android恶意软件检测提供了有用的信息。自从Shabtai方法在移动设备上进行的,它比我们的方法消耗更多的资源,而在表<a href="//www.newsama.com/journals/scn/2020/8630748/tab10/" target="_blank">10</a>。</p> <div class="floats-partial-section partial-other-wrapper" data-section="tab10"> <div class="floats-partial-content fig-content-tab10"> <table class="table-group" id="tab10"> <tbody> <tr> <td> <table class="table"> <tbody> <tr> <td class="thead-hr" colspan="3"> <hr></td> </tr> <tr class="thead"> <td class="align_left"></td> <td class="align_center">该方法</td> <td class="align_center">Shabtai的方法</td> </tr> <tr> <td class="thead-hr" colspan="3"> <hr></td> </tr> <tr> <td class="align_left">精度</td> <td class="align_center">96.9%</td> <td class="align_center">77.1%</td> </tr> <tr> <td class="align_left"><i>F</我>测量</td> <td class="align_center">0.940</td> <td class="align_center">0.695</td> </tr> <tr> <td class="align_left">平均能耗</td> <td class="align_center">1.2%</td> <td class="align_center">7.7%</td> </tr> <tr> <td class="align_left">平均CPU消耗</td> <td class="align_center">0.6%</td> <td class="align_center">2.3%</td> </tr> <tr> <td class="align_left">平均内存消耗</td> <td class="align_center">6.54 MB</td> <td class="align_center">9.37 MB</td> </tr> <tr class="table-tr"> <td colspan="3"> <hr class="tbody-hr"></td> </tr> </tbody> </table></td> </tr> </tbody> </table> </div> <div class="floats-partial-footer"> <div class="floats-partial-caption"> <span class="caption-text">表10</span> <a aria-label="full view" class="caption-partial-url" href="//www.newsama.com/journals/scn/2020/8630748/tab10/" title="" target="_blank"></a> </div> <div class="floats-partial-caption-text"> 该方法的比较与Shabtai的方法。</d我v> </div> </div> <h4 id="discussion">7所示。讨论</h4> <p>我们广泛的实验的结果表明,重新包装Android恶意软件可以有效地和有效地检测到集群网络流量在边缘设备。然而,仍然有对我们的方法的局限性。首先,我们假设大多数的设备已经安装了原始应用程序(<span class="inline_break"> <svg height="11.5564pt" id="M82" style="vertical-align:-2.26807pt" version="1.1" viewbox="-0.0498162 -9.28833 16.751 11.5564" width="16.751pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,0,0)"> <use xlink:href="#g113-115"></use> </g> <g transform="matrix(.013,0,0,-0.013,9.12,0)"> <use xlink:href="#g117-91"></use> </g> </svg><span class="irelop"></span> <svg height="11.5564pt" style="vertical-align:-2.26807pt" version="1.1" viewbox="20.3331838 -9.28833 16.094 11.5564" width="16.094pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,20.383,0)"> <use xlink:href="#g113-41"></use> </g> <g transform="matrix(.013,0,0,-0.013,24.881,0)"> <use xlink:href="#g113-50"></use> </g> <g transform="matrix(.013,0,0,-0.013,31.121,0)"> <use xlink:href="#g113-48"></use> </g> </svg><span class="isep"></span><span class="nowrap"> <svg height="11.5564pt" style="vertical-align:-2.26807pt" version="1.1" viewbox="36.4321838 -9.28833 18 11.5564" width="18pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"> <g transform="matrix(.013,0,0,-0.013,36.482,0)"> <use xlink:href="#g113-51"></use> </g> <g transform="matrix(.013,0,0,-0.013,42.722,0)"> <use xlink:href="#g113-42"></use> </g> <g transform="matrix(.013,0,0,-0.013,47.22,0)"> <use xlink:href="#g113-118"></use> </g> </svg>,</span></span>节中描述<a href="#sec5.1">5.1</a>)。这在大多数情况下是合理的,因为手机用户通常从官方下载的应用程序市场。然而,等官方市场的地区禁止使用谷歌,亚马逊,可能大多数移动设备重新打包的应用程序安装。这可能导致假阳性。第二,如果恶意软件没有产生足够的流量,我们的方法无法检测它。例如,一些恶意软件只发送短信欺诈溢价。这种类型的恶意软件不能检测到其网络流量监控。第三,我们依赖于第三方工具如Virustotal识别恶意url并减少假警报的数量。如果恶意应用租金法律平台等公共云作为远程控制服务器,我们的方法将会判断这是一个正常的应用程序。因此,假阴性将生成。</p> <p>为了克服这些限制,我们可以将该方法与SAMADroid等可用方法。在这种情况下,edge-client应用不仅会记录流元也监控应用系统的行为。然而,系统行为监控不需要进行。如果检测到异常但无害或低流量应用,edge-client应用将通知记录相应的应用程序的系统行为。同样,edge-client应用程序可以发送应用程序系统行为到边缘服务器进行进一步处理。这种结合方法的性能将在我们未来的评估工作。人们还可以把拟议的框架与AppFA [<a href="#B14">14</a>为其他类型的Android恶意软件的检测。例如,边缘提取应用交通行为特性和云可以比较应用程序的行为与他们的同辈群体识别异常。此外,我们可以首先使用集群技术(<a href="#B60">60</a>]组重新打包应用程序根据相同的恶意的行为模块,然后分析每组代表重新打包应用程序来获得更精确的行为特性。</p> <p>边缘计算的范例是用来检测Android恶意软件在这个研究。然而,在实践中会遇到的一些挑战当部署它:第一,移动设备必须安装指定的应用程序收集必要的信息,这可能会导致问题和移动用户可以拒绝合作。第二,在边计算,应该是预处理的数据优势更好地保护用户的隐私。然而,边缘服务器可以观察到的所有数据(包括敏感信息),威胁到用户的隐私。例如,如果边缘部署云提供商,用户的隐私信息也可以到云上。没有区别的隐私保护,除非user-cloud模型边缘服务器部署的用户。第三,边缘服务器应该免受网络攻击。否则,它将方便黑客窃取用户的私人信息。</p> <h4 id="conclusion">8。结论</h4> <p>在本文中,我们提出一种新颖的基于边缘检测Android恶意软件的方法计算。我们所知,Android恶意软件利用边缘检测计算和交通集群之前没有考虑。通过引入边缘层,移动设备的主要任务卸载到边缘服务器和移动设备只需要记录流的元,大大节约了资源的移动设备。边缘服务器提取应用程序的网络流量特性和向云平台发送这些特性进行进一步分析。因此,可以更好的保护用户的隐私。收到特性,云计算应用程序的相似性和集群这些相似性值自动分离原始应用程序和恶意软件。400 Android应用程序,我们评估我们的方法和实验结果表明,该检测几个应用程序,精度可以达到100%,平均精度为96.9%。我们还测试了该方法的性能,并与典型的方法。比较结果表明,我们的方法可以检测重新包装Android恶意软件与更高的检测精度和更低的权力和资源消耗。在未来,我们将继续努力克服了限制和评估该方法在真实世界的场景。</p> <h4 id="data-availability">数据可用性</h4> <p>下载的应用程序用于支持本研究的发现已被存入<a href="https://pan.baidu.com/s/1b8vMceIdtdd1gBRC5Gbzvw" target="_blank">https://pan.baidu.com/s/1b8vMceIdtdd1gBRC5Gbzvw</a>。其提取vd5r代码。聚类的代码也在存储库中。因为应用程序的网络流量包含用户的敏感信息,不能公开共享。然而,我们已经解释了所有的步骤自动生成网络流量。这些步骤也描述的指令。pdf在存储库中。</p> <h4 id="conflicts-of-interest">的利益冲突</h4> <p>作者宣称没有利益冲突。</p> <h4 id="acknowledgments">确认</h4> <p>这项工作是由中国国家关键技术研究与发展计划下授予2018 yfd0401404,中国国家自然科学基金资助下61702282,61802192,和71801123,自然科学基金资助下的中国江苏高等教育机构18 kjb520024和17 kjb520023下南京林业大学拨款GXL016 CX2016026, NUPTSF格兰特NY217143之下。</p> </div> <div class="xml-content"> <h4 class="references" id="references">引用</h4> <ol> <li id="B1">Statista,<我>全球手机操作系统的市场份额从2012年1月至2019年12月</我>2009年,Statista,汉堡,德国,<a target="_blank" 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Liu et al." target="_blank">谷歌学术搜索</a></span></li> </ol> </div> <div class="xml-content"> <h4 class="copyright" id="copyright">版权</h4> <p>版权©2020高峰等。这是一个开放的分布式下文章<a rel="license" href="http://creativecommons.org/licenses/by/4.0/">知识共享归属许可</a>,它允许无限制的使用、分配和复制在任何媒介,提供最初的工作是正确引用。</p> </div> </div> </article> </div> </div> </div> <div class="biblio__Wrapper-sc-1nou1lz-0 eyHfWh journal_article__BiblioIntegratorWidget-sc-12fk6zy-6 bqUtxN article_widget biblioWrapper hide"> <hr> <h4 class="biblio__H4-sc-1nou1lz-2 kgAKHb hrTitleRef">更多相关文章</h4> <div id="biblio_widget" class="biblio__BiblioWrapper-sc-1nou1lz-1 dhicaS"></div> </div> </div> </div> <div class="threeColumn__RightWrapper-sc-1bf4078-2 sZeeW rightWrapper"> <div id="rightSectionMenu" class="sc-hZSUBg hwTmaF journal_article__StickyRight-sc-12fk6zy-0 xuPEv"> <div class="journal_article__ArticleStickyTopToolbar-sc-12fk6zy-1 iKpUSJ article_sticky_top_toolbar"> <div class="sc-jrIrqw deaPpH article_top_toolbar"> <div class="sc-hjRWVT iLecBy 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height="20"></a> <a class="sc-htpNat bUhGXt link sc-cbkKFq dNPgJJ sc-iQtOjA huyqUq ref_desktop" href="//www.newsama.com/journals/scn/2020/8630748.ris" aria-label="" target="" id="toolbar__dcNavLarge"><span><img alt="" class="sc-EHOje fEOMwM sc-krvtoX isUmzT" title="" role="presentation" src="data:image/svg+xml;base64,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" height="24"><span class="text">下载引用</span></span><img alt="" class="sc-EHOje ggEPYc sc-fYiAbW eBEQa fileArrow" title="" role="presentation" src="data:image/svg+xml;base64,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" height="20"></a> <a class="sc-htpNat bUhGXt link sc-cbkKFq dNPgJJ sc-fHxwqH dPWBKK ref_desktop" href="//www.newsama.com/journals/scn/2020/8630748.ris" aria-label="" target="" id="toolbar__dcNavSmall"><span><img alt="" class="sc-EHOje fEOMwM sc-krvtoX isUmzT" title="" role="presentation" src="data:image/svg+xml;base64,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" height="24"><span class="text">引用</span></span><img alt="" class="sc-EHOje ggEPYc sc-fYiAbW eBEQa fileArrow" title="" role="presentation" src="data:image/svg+xml;base64,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" height="20"></a> </div> </div> <div class="journal_article__ArticleStickyBottomToolbar-sc-12fk6zy-2 gvAMNw article_sticky_bottom_toolbar"> <div class="sc-fyjhYU bmCmNg article_bottom_toolbar"> <div class="sc-ugnQR bdNavy accordion" property="background-color" color="#D8D8D8" id="toolbar__dofNav"> <span><img alt="" class="sc-EHOje fEOMwM sc-iomxrj czMNsj" title="" role="presentation" src="data:image/svg+xml;base64,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" height="24"><span class="sc-iFMziU gCiAsp">下载其他格式</span><span class="sc-keVrkP hYjHxB">更多的</span></span> <img alt="" class="sc-EHOje fEOMwM sc-dvCyap bivFoZ" title="" role="presentation" src="data:image/svg+xml;base64,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" height="24"> </div> <div class="sc-eIHaNI qcTAH"> <a class="sc-htpNat bUhGXt link sc-eTpRJs eqSlZb open_panel" href="//www.newsama.com/downloads/journals/scn/2020/8630748.epub" aria-label="ePub" property="background-color" color="#D8D8D8"> <div class="sc-dxZgTM jwQjXi"> ePub</d我v><img alt="" class="sc-EHOje fEOMwM sc-iomxrj czMNsj" title="" role="presentation" 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href="//www.newsama.com/journals/" aria-label="Journals"><img alt="" class="sc-EHOje jRIjVn" title="" role="presentation" src="data:image/svg+xml;base64,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" height="14">期刊</a></li> <li><a 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src="data:image/svg+xml;base64,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" height="14">文章处理费用</a></li> <li><a class="sc-htpNat bUhGXt link subscriptions" href="//www.newsama.com/subscriptions/" aria-label="Subscriptions"><img alt="" class="sc-EHOje jRIjVn" title="" role="presentation" src="data:image/svg+xml;base64,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" height="14">订阅</a></li> </ul> <ul class="_2k5c8zEhMT-84kRD4oDgAz _1SoDWGr_FVsil9klRfjnhb"> <li><a 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class="sc-EHOje jRIjVn" title="" role="presentation" src="data:image/svg+xml;base64,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" height="14">编辑器</a></li> <li><a class="sc-htpNat bUhGXt link reviewers" 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