The Prediction Algorithm of Network Security Situation Based on Grey Correlation Entropy Kalman Filtering

Based on the review of current prediction algorithms of network security situation, prediction algorithms based on Kalman filtering are studied. A prediction algorithm of network security situation based on grey correlation entropy Kalman filtering is presented, hoping to be more helpful to network administrators through providing them information more effectively. First correlation of factors influencing network security situation is analyzed by Grey correlation entropy analysis method, and key influencing factors are selected. Then according to these influencing factors corresponding process equation and prediction equation are established. Finally, network security situation prediction is made recursively by Kalman filtering. Experiment results show that the prediction by this method is more precise compared to GM(1, 1) and general Kalman algorithm, and its real-time performance is better than RBF algorithm.