Network Node Resource Risk Assessment Based on Bayesian Belief Network Model

Abstract

Network attacks will bring network node resource risks. In this paper, the time series of memory usage rate, network traffic and CPU utilization rate are selected as the research objects, and the network node resources are interrelated. Based on this feature, a network node resource risk assessment method based on Bayesian belief network is designed, and the single risk and total risk of network node resources are quantified. The results show that this method can effectively evaluate the network node resource risk, and fully consider the internal correlation between network node resources, and provide a new method for risk assessment of network node resources. The effect of this method is better than the traditional K-Means clustered method and decision tree method.