Research on the Application of Intelligent Learning Algorithms in Network Security Situation Awareness and Prediction Methods

Abstract

As the core hotspot of network information security, network security situational awareness has received more and more attention. In order to explore the application effect of intelligent learning algorithm, this study takes Radial Basis Function (RBF) as the main research object, optimizes RBF by Simulated Annealing (SA) algorithm and Hybrid Hierarchy Genetic Algorithm (HHGA), constructs RBF neural network prediction model based on SA-HHGA optimization, and carries out relevant experiments. The results show that the predicted situation value of the optimized RBF in 15 samples is very close to the realistic situation value. RBF has good prediction effect and can provide assistance for the maintenance of network security.