Dynamic probabilistic risk assessment for electric grid cybersecurity

Xiaoxu Diao, Yunfei Zhao, Carol Smidts, Pavan Kumar Vaddi, Ruixuan Li, Hangtian Lei, Yacine Chakhchoukh, Brian Johnson and Katya Le Blanc

Reliability Engineering and System Safety, 2024, vol. 241, issue C

Abstract: Electric grid cybersecurity risk has become a significant concern of industries and governments. This paper proposes a dynamic probabilistic risk assessment method for electric grid cybersecurity risk analysis. The proposed method helps reduce the reliance on expert judgment, capture a broad range of components and system dynamics, and model the interactions between various contributing entities (e.g., attacker, operator). In addition, the scenarios with multiple events, such as the occurrence of both cyberattacks and failures of physical components, the occurrence of both cyberattacks and operators’ (in)correct reactions, are considered and analyzed. For each cyberattack scenario, Monte Carlo simulations are used to obtain possible sequences of the system's evolution under study and then derive risk estimates. As an application of the proposed method, the risk assessment method serves as the basis of risk-informed defense resource allocation to improve electric grid cybersecurity. The proposed method is verified using the IEEE 14-bus system by evaluating different security resource allocations for selected cyberattack scenarios.

Keywords: Dynamic Probabilistic Risk Assessment; Cybersecurity risk; Electric grid systems (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:241:y:2024:i:c:s0951832023006130

DOI: 10.1016/j.ress.2023.109699

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