Multidimensional Detection and Evaluation System of Computer Network Security Based on Machine Learning Algorithm
Honghao Bai, Yuru Weng, Qi Zhao, Jiabin Guan · 2022 IEEE 2nd International Conference on Mobile Networks and Wireless Communications (ICMNWC) · 2022
With the continuous development of computer technology, the problem of network security has become increasingly prominent. Traditional cryptography methods can hardly guarantee the security of personal information, property and privacy. In order to evaluate and study machine learning algorithms and make them more convenient and less costly in real life, it has become a very important topic in the current computer field. This paper first introduces the machine learning algorithm and cryptography, and the current research status at home and abroad. Secondly, it proposes intrusion detection system based on random space model, artificial neural network method and other defense strategies. Finally, a machine learning algorithm that uses clustering analysis to classify and store different kinds of feature information and realize multidimensional identity recognition is given, and MATLAB is used in the computer network security attack early warning simulation experiment. Finally, the experimental results show that the multi-dimensional detection and evaluation system performs well in the accuracy and time of malware detection, and the false detection rate is very low. This shows that the performance of the system can meet the needs of users.