Artificial Neural Network Inducement for Enhancement of Cloud Computing Security

Md. Raihan Uddin, Kh. Mohaimenul Kabir, Md. Taslim Arefin
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Abstract

Cloud computing is a spirited topic in this epoch where IOT introducing the modern lifestyle. These embrace cost-effectiveness, time savings and the actual arrangement of computing properties. Conversely, in Cloud Computing privacy and security is a big issue where there are many kinds of thread and attack are working rapidly. In the context, the best cryptographic method AES algorithm and AI-based method ANN have chosen to work for the enhancement of the security where cloud computing demands the highest priority. In this case, this paper is proposing the highly advanced two-step security layer for cloud computing. Primarily, AES provides for the first layer security of the first stratum. In the AES algorithm, the execution is dependent on the key size of the algorithm when the number of rounds to be accomplished. A MATLAB code is developed for plaintext encryption and cipher text decryption. Experiments are conducted to measure execution times. ANN is a method of computation which is biologically stimulated. These only look like the parallel computation generated which are the basics of human learning by the biological neural network. Iris and Finger recognition is implemented using MATLAB through ANN. The paper demonstrated the great proficiency of the proposed system for the user purpose.
增强云计算安全的人工神经网络诱导
在物联网引入现代生活方式的时代,云计算是一个充满活力的话题。这些包括成本效益、时间节省和计算属性的实际安排。相反,在云计算中,隐私和安全是一个大问题,因为有许多种类的线程和攻击正在快速工作。在这种情况下,最好的加密方法AES算法和基于人工智能的ANN方法被选择用于云计算要求最高优先级的安全性增强。在这种情况下,本文提出了高度先进的云计算两步安全层。AES主要提供第一层的第一层安全性。在AES算法中,执行取决于要完成的轮数时算法的密钥大小。开发了一个用于明文加密和密文解密的MATLAB代码。通过实验来测量执行时间。人工神经网络是一种受生物刺激的计算方法。这些只是看起来像由生物神经网络生成的并行计算,这是人类学习的基础。利用MATLAB通过人工神经网络实现虹膜识别和手指识别。本文证明了所提出的系统对用户目的的极大精通。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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