Computer network security evaluation simulation model based on neural network

The computer network security evaluation simulation model is analyzed based on neural network. Firstly, based on the system security experimental platform, the system security detection algorithm is constructed, and the selection strategy of calculation scale is analyzed. The Prefix Span algorithm is introduced, improving its algorithm. Data mining based on Prefix is carried out, with the relationship between intrusions and their relationships analyzed. Secondly, the implementation steps of the algorithm are explained. Finally, the algorithm is tested, and the results are analyzed from three aspects: entropy value feature, active entropy algorithm and cloud platform performance. The conclusion is that the algorithm designed in this paper has good accuracy and adaptability, and it can play a good supporting role in system safety practice training, and the encryption protocol in the network security protocol is further improved, which has laid a solid foundation for the security development of the network.