Research on the Application of GABP Neural Network Algorithm Model in Computer Network Security Assessment

Network security is an important issue facing current network security. This project takes the traditional BP neural network as the research object and network security factors as the research object. It uses the global optimization function of the genetic algorithm to build a nonlinear model of network security factors, expands its scope of application, and improves the generalization ability of the neural network. This paper provides theoretical basis for the assessment and prediction of network risks and network security situations. Through case analysis, it is proved that the method of using GABP neural network for network security evaluation and forecasting can maintain the overall security comprehensive level of the network at a very high situation value level, and provide an effective method for network security early warning and management.