Attack path prediction based on Bayesian game model

Abstract

The current network risk assessment model often ignores the impact of attack cost and intrusion intention on network security. In order to better solve the problem of information security defense strategy selection and accurately assess the target network risk, this paper proposes an attack path prediction method based on game model.The atomic attack probability is calculated by vulnerability value, attack cost and attack benefit. The static risk assessment model is established combined with Bayesian belief network quantitative attack graph. And the dynamic update model of intrusion intention is used to realize the effective prediction of attack action under rational assumption, which provides the basis for dynamic defense measures of attack surface. The experimental results verify the feasibility and effectiveness of the model and method.