Network Security Prediction Method Based on Kalman Filtering Fusion Decision Entropy Theory
Liang Huang, Xinhao Chen, Xinsheng Lai · International Journal of Security and Its Applications · 2016
Network security situation prediction is of great significance for the use of the Internet, and it is the focus of production and life issues.Under the guidance of the model combination forecasting method, In this paper, based on the Kalman filtering model a new method of network security prediction is presented, which is based on the theory of decision entropy.In this method, the Kalman state equation and measurement equation are constructed according to the key attributes of the network security state, and then combined with the decision entropy theory to predict the future state of network security.The experimental results show that the proposed method has high prediction accuracy and is suitable for the state prediction of network security.