TY -的A2 -汗,爱迪盟——哈桑,穆罕默德Kamrul AU -沙菲克,默罕默德盟——伊斯兰教,Shayla AU - Pandey, Bishwajeet AU -贝克El-Ebiary尤瑟夫a . AU -纳Nazmus瓶非盟- Ciro罗德里格斯,r . AU -巴尔加斯,多丽丝Esenarro PY - 2021 DA - 2021/04/05 TI -轻量级密码算法在复杂的物联网应用程序猜测攻击保护SP - 5540296六世- 2021 AB -作为世界上不断发展,需要自动互联设备已经开始获得意义;为了迎合的条件,一个新的概念引入了物联网(物联网),围绕智能设备ʼ观念。这些智能设备使用物联网可以通过网络互相沟通达到特定的目标,即。、自动化和智能决策。物联网使机器的用户将他们的家庭负担这些复杂的机器后,相应的环境变量和控制他们的行为。很明显,这些机器使用传感器收集重要信息,然后计算节点的复杂性进行了分析,然后潇洒地控制这些设备ʼ操作行为。深上优于猜测攻击保护算法已经加强物联网安全;然而,它仍然有一个复杂的行业的物联网网络的关键挑战。这种系统的至关重要的一个方面是需要有一个重要的处理大数据量的网络训练时间ʼ年代之前的数据流。传统的深度学习方法包括决策树、逻辑回归和支持向量机。然而,至关重要的是要注意,这个方便的是要付出代价,包括物联网网络安全漏洞很容易被黑客可以访问干扰传感器/通信数据,后来利用恶意目的。 This paper presents the experimental study of cryptographic algorithms to classify the types of encryption algorithms into the asymmetric and asymmetric encryption algorithm. It presents a deep analysis of AES, DES, 3DES, RSA, and Blowfish based on timing complexity, size, encryption, and decryption performances. It has been assessed in terms of the guessing attack in real-time deep learning complex IoT applications. The assessment has been done using the simulation approach and it has been tested the speed of encryption and decryption of the selected encryption algorithms. For each encryption and decryption, the tests executed the same encryption using the same plaintext for five separate times, and the average time is compared. The key size used for each encryption algorithm is the maximum bytes the cipher can allow. To the comparison, the average time required to compute the algorithm by the three devices is used. For the experimental test, a set of plaintexts is used in the simulation—password-sized text and paragraph-sized text—that achieves target fair results compared to the existing algorithms in real-time deep learning networks for IoT applications. SN - 1076-2787 UR - https://doi.org/10.1155/2021/5540296 DO - 10.1155/2021/5540296 JF - Complexity PB - Hindawi KW - ER -