KEYWORDS: Network security, Control systems, Information security, Risk assessment, Process control, Computer security, Defense and security, Security technologies, Power grids, Systems modeling
The industrial control systems of new energy power plants are becoming increasingly complex and diversified, and there are also protective isolations between various industrial control systems, resulting in insufficient overall network security monitoring and defense capabilities of new energy power plants. In order to solve this problem, this paper studies a network security situational awareness solution for new energy industrial control systems. This solution is an industrial control security protection method for new energy power plants based on probabilistic attack graphs. First, knowledge graph technology is used to semantically associate security metadata such as devices, vulnerabilities, and topologies, and a cross-domain attack graph generation algorithm is used to automatically generate a cross-domain attack graph; then, based on the cross-domain attack graph, the basic attributes of vulnerabilities and The time-varying characteristics of threats are incorporated into risk propagation probability calculations, thereby enabling quantitative analysis of cross-domain dynamic security risks in new energy power plant industrial control systems. Experimental results show that this method realizes automated cross-domain dynamic security risk analysis of new energy power plant industrial control systems, and effectively improves the overall network security protection capabilities of new energy industrial control systems.
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