Design of Computer Network Security Evaluation Model Based on Deep Neural Network Model

Computer network is a complex network, so it is necessary to comprehensively consider all the factors that can affect the network security, so as to make the evaluation index of computer network more rigorous. In the process of designing the computer network security evaluation (CNSE) system, it is necessary to comprehensively analyze the relevant computer security factors. In order to make CNSE more stable and safe, and to effectively improve the accuracy of evaluation, this paper attempts to apply neural network technology to comprehensive evaluation of network security, and generates training samples, inspection samples and test samples needed to establish neural network model by randomly selecting values within the single index evaluation standard. Under the condition of following the basic principles and steps of BP network modeling, a reliable and effective comprehensive evaluation model of network security is established. The simulation results show that, compared with the traditional CNSE model, the speed of CNSE based on particle optimization neural network is faster and the accuracy of CNSE can be improved.