A Method of Network Security Situation Prediction Based on Gray Neural Network Model

Abstract:

In this paper, a new network security situation intelligent analysis prediction method is proposed, which applies GM(1,1) model and BP neural network model in the analytic prediction field of network security situation information, and combination and optimization is performed to it to improve the accuracy of network security situation prediction. By analyzing and calculating the great amount of information acquired from network security situation evaluation system, it is able to make prediction on the current security situation of network system and the its future change trend, and make and implement relative response strategy according to prediction results, and reduce the harm from network attacks and improve the emergency response ability of network information system, so that we can make preparation before great damage occurs and reduce or avoid any possible attack to ensure the smooth running of system. The experiment results show that this method is a better solution for network security situation prediction.

• Periodical: Applied Mechanics and Materials (Volumes 63-64)
• Pages: 936-939
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.63-64.936
• Online since: June 2011
• Authors: Nian Liu, Geng Li, Yong Liu
• Keywords: Gray Theory, Network Security, Neural Network (NN), Security Situation Prediction

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