基于微分流形的网络攻防效用度量方法

Network security methods lack effective metrics to measure attack risks and defense capabilities in dynamic networks, especially since they have high dimensionality and are difficult to analyze since there are many indicators. This paper presents a method to quantify network attack and defense capabilities. Clustering and principal component analyses are used to reduce the dimensionality and allocate weights to the indicator groups. These indexes are embedded in differential manifolds that change with time with the network risk evaluated based on the attack risks and defense capabilities to quantify the network security effectiveness. The CIC2017 dataset is used as an example to show that this method can indicate the attach and defense risks for dynamic networks. The results show that this method can provide a dynamic method for network security measurements.