基于机器学习的数据加密技术在计算机网络安全中的应用研究

Yufei Song, M. Chu
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引用次数: 1

摘要

如今,在网络时代,计算机安全问题引起了人们的广泛关注。为了保证计算机网络的安全,有必要重视改进数据加密技术。数据加密技术主要分为两种:非对称密钥和对称密钥。通常,发送方和接收方使用不同的密码设置来实现网络安全。本文提出了一种将机器学习分类算法应用于同态加密数据集的方案:首先对明文进行预处理,使其满足数据同态加密的要求;然后,按协议对加密后的数据集进行比较和排序。最后,得到分类结果。结合机器学习算法,控制文本信息隐藏收敛性,优化文本信息隐藏算法。仿真结果表明,该方法可以将文本信息隐藏在更高的深度,具有更强的抗攻击能力,从而提高了文本信息存储的安全性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the Application of Data Encryption Technology in Computer Network Security Based on Machine Learning
Nowadays, in the network age, computer security issues have attracted much attention. In order to ensure computer network security, it is necessary to pay attention to improving data encryption technology. Data encryption technology is mainly divided into two types: asymmetric key and symmetric key. Generally, the sender and receiver use different password settings to realize network security. In this paper, a scheme of applying machine learning classification algorithm to homomorphic encrypted data sets is proposed: firstly, the plaintext is preprocessed to ensure that it meets the requirements of homomorphic encryption of data; Then, compare and sort the encrypted data set by protocol. Finally, the classification results are obtained. Combined with machine learning algorithm, the text information hiding convergence is controlled, and the text information hiding algorithm is optimized. Simulation results show that this method can hide text information in a higher depth, and has stronger anti-attack ability, thus improving the security of text information storage.
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