Measuring the Network Vulnerability Based on Markov Criticality

Vulnerability assessment-a critical issue for networks-attempts to foresee unexpected destructive events or hostile attacks in the whole system. In this article, we consider a new Markov global connectivity metric-Kemeny constant, and take its derivative called Markov criticality to identify critical links. Markov criticality allows us to find links that are most influential on the derivative of Kemeny constant. Thus, we can utilize it to identity a critical link (i, j) from node i to node j, such that removing it leads to a minimization of networks' global connectivity, i.e., the Kemeny constant. Furthermore, we also define a novel vulnerability index to measure the average speed by which we can disconnect a specified ratio of links with network decomposition. Our method is of high efficiency, which can be easily employed to calculate the Markov criticality in real-life networks. Comprehensive experiments on several synthetic and real-life networks have demonstrated our method's better performance by comparing it with state-of-the-art baseline approaches.

Automated summary

This article introduces a new method for assessing Markov criticality, which can effectively identify critical links in networks. Additionally, a novel vulnerability index is proposed to measure the vulnerability level in networks. Experimental results demonstrate that this method outperforms existing baseline approaches in terms of overall performance.