Research on gray correlation analysis and situation prediction of network information security

Abstract In order to further improve the accuracy and efficiency of network information security situation prediction, this study used dynamic equal-dimensional method based on gray correlation analysis GM (1, N) model carried out an experiment designed prediction (NSSP) in a simulated environment. It was found that predicted result improved closer actual value. Taking 11th hour as example, value 28.1524, which only 0.8983 larger than value; compared with neural Markov models, error smaller: average 2.3811, 67.88% 70.31% smaller other two models. The had time complexity 49.99% 39.53% lower models; thus, it high computational efficiency. experimental results verify effectiveness solving NSSP problem. can be promoted applied practice deployed schools enterprises achieve security.