PSO-BPNN-Based Prediction of Network Security Situation

Under the application background of network security evaluation research, this paper proposes a method of situation prediction based on particle swarm optimization (PSO) for optimizing BP neural network (BPNN). It uses PSO to reach global optimization of BP network´s weight value and threshold value, and then by means of the optimized BP network builds a prediction model to predict the future network security situation. Experiment results show that this method can overcome the shortage of the predicting application in the traditional BP network, and effectively improve the accuracy of situation prediction. It can be applied into the situation prediction of network security situation awareness.