Information Network Security Situation Prediction Method Based on Particle Swarm Optimization

With the gradual popularization of the Internet and the rapid development of emerging technologies such as the Internet of Things, Big data and cloud computing, network security has been threatened by serious intrusion. At present, most of the existing security protection devices operate independently and can only detect and protect a certain part of the network. On this basis, a new network situation prediction method is proposed. The solution to the problem of network security situation evaluation is actually to analyze the indicators that affect the network security situation, quantify these indicators, and then get an evaluation grade through some evaluation algorithms. What kind of evaluation algorithm to use is the key content of network security situation research, because a reasonable evaluation algorithm directly affects the correctness of the final evaluation result. Because of this, this paper chooses the evaluation algorithm as the main research content, carefully studies a variety of evaluation algorithms, and finally chooses the support vector machine method to evaluate the network security situation. It is proved that the algorithm has better optimization performance.