A Dynamic Risk Assessment Method for Industrial Control Network Security Based on Bayesian Attack Graph
Wei Hong Yang, Fangyuan Hou, Zhuoyue Jia, Wang Hu, Yu Kai Yao, Peng Yin, Xinyue Xu, Siyu Liu · 2025
With the advancement of information and communication technology, industrial control systems (ICS) are facing increasing cybersecurity challenges. Traditional risk assessment methods neglect the interdependencies between nodes and fail to capture systemic risks, making them insufficient for addressing the complexity of modern ICS environments. By integrating an improved CVSS, this paper proposes a dynamic risk assessment method for ICS based on Bayesian Attack Graphs, specifically adapted for industrial environments. The method begins with assessing individual vulnerability risks and progressively extends to overall network risk evaluation, enabling comprehensive static and dynamic risk assessments tailored to industrial control systems.