Research on the Application of Data Encryption Technology in Computer Network Security Based on Machine Learning

Abstract

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.