A Probabilistic Computing Approach of Attack Graph-Based Nodes in Large-scale Network

Abstract To protect critical resources in networked environments, it is important to quantify the likelihood of potential multi- step attacks in attack graphs. Aimed at the problems that probabilistic incorrect computing caused by shared dependencies in nodes, a methodology for security risk analysis that is based on the model of attack graphs and the Common Vulnerability Scoring System (CVSS) was presented, and the problem of probabilistic incorrect computing was solved successfully by proposing the probabilistic computing approach of accurate calculation and approximate calculation, While ensuring the accuracy of the probability of attack graph-based nodes, quickly Calculated the probability of each node, which can be adapted to a large-scale network. Reasonableness and effectiveness of proposed method was verified in the simulation. Compared with the related research, our approach can be adapted to a more complex attack graph, and had good scalability.