Journal of Modern Power Systems and Clean Energy

ISSN 2196-5625 CN 32-1884/TK

Security Risk Assessment and Risk-oriented Defense Resource Allocation for Cyber-physical Distribution Networks Against Coordinated Cyber Attacks
Author:
Affiliation:

1.School of Electrical Engineering, Southeast University, Nanjing210096, China;2.College of Automation and College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing210023, China;3.Shenzhen Power Supply Bureau Co., Ltd., Shenzhen518001, China

Fund Project:

This work was supported by the National Natural Science Foundation of China (No. 52377086) and the Postgraduate Research & Practice Innovation Program of Jiangsu Province (No. SJCX23_0063).

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    Abstract:

    With the proliferation of advanced communication technologies and the deepening interdependence between cyber and physical components, power distribution networks are subject to miscellaneous security risks induced by malicious attackers. To address the issue, this paper proposes a security risk assessment method and a risk-oriented defense resource allocation strategy for cyber-physical distribution networks (CPDNs) against coordinated cyber attacks. First, an attack graph-based CPDN architecture is constructed, and representative cyber-attack paths are drawn considering the CPDN topology and the risk propagation process. The probability of a successful coordinated cyber attack and incurred security risks are quantitatively assessed based on the absorbing Markov chain model and National Institute of Standards and Technology (NIST) standard. Next, a risk-oriented defense resource allocation strategy is proposed for CPDNs in different attack scenarios. The trade-off between security risk and limited resource budget is formulated as a multi-objective optimization (MOO) problem, which is solved by an efficient optimal Pareto solution generation approach. By employing a generational distance metric, the optimal solution is prioritized from the optimal Pareto set of the MOO and leveraged for subsequent atomic allocation of defense resources. Several case studies on a modified IEEE 123-node test feeder substantiate the efficacy of the proposed security risk assessment method and risk-oriented defense resource allocation strategy.

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History
  • Received:March 16,2024
  • Revised:May 23,2024
  • Adopted:
  • Online: January 24,2025
  • Published: