Abstract

By analyzing the impact of cyber attack on the cyber physical power system (CPPS), a Bayesian based on petri net(BBPN) quantitative risk assessment method was proposed in this paper. Petri net as an important formal tool for modeling, analysis and analysis of distributed, parallel and real-time systems provides a solid foundation for CPS modeling. However, Petri nets lack the ability to describe spatial information, so it is impossible to fully model CPS. Incorrect system modeling can directly affect system reliability and even life-threatening and property safety, Therefore, when modeling and analyzing CPS characteristics, a more complete modeling method is needed. This paper extends the Defect extension time Petri net and constructs a spatiotemporal Petri net that can describe the positional changes of CPS physical entities. This paper also analyzes the physical characteristics of CPS in detail, starting from the classification and characteristics of physical entities, and deeply studying the properties of CPS physical entities and their location transition process. Proposing a formal modeling method for CPS physical entities; Introducing spatial factors on the basis of Petri nets by analyzing the characteristics that Petri nets must satisfy, getting the formal definition of Petri net, It can not only describe the physical entity logic and time-level behavior, but also describe the state changes caused by physical entity location changes.Firstly, using petri net to finely model important equipment in information systems, and then based on these models and the attack source delivery path, establishing the fine Bayesian cyber attack model. With the combination of the observed real-time attack events, we dynamically update the probability of attack behavior based on Bayesian reasoning. Finally, we proposed the optimal load control algorithm considering the node failure, comprehensive quantitative assessing the impact of cyber attacks on the CPPS.

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