Optimal defense resource allocation against cyber-attacks in distributed generation systems

Huadong Mo, Xun Xiao, Giovanni Sansavini and Daoyi Dong

Journal of Risk and Reliability, 2024, vol. 238, issue 6, 1302-1329

Abstract: The deployment of advanced information and communication technologies necessitates considering new security threats, such as distributed denial of service attacks and malware, which can fault power generators and feeders and exacerbate power outages in distributed generation systems (DGS). Existing cyber-security studies fail to validate the attacker–defender game model between operators and hackers or provide a DGS model that accounts for realistic characteristics and operations. Furthermore, current game models may be infeasible for large-scale systems and are not robust against uncertainties owing to the use of metaheuristic algorithms. To overcome these gaps, this study quantified the result of a game using the contest success function and estimated the parameters of this function based on real-world evidence: the dataset of cyber crime incidents from Advisen, US. The DGS management was optimized using the power flow model considering the scenario-based uncertainty stemming from cyber-attacks. A three-stage attack+defend–defend–attack framework is proposed to optimize attack–defense resource allocation using the cooperative game and ϵ -subgradient method. The results for IEEE 4, 13, 34, 123 and 342 test node feeders show that the proposed framework is applicable to large-scale systems and robust to various types of cyber-attacks. The proposed model and algorithms further enhance the DGS performance under uncertainties by protecting the entire grid or only critical nodes according to the defenders’ objectives.

Keywords: Attack consequence-based cluster; cooperative game; distributed denial of service; distributed generation systems; scenario-based uncertainty; ϵ-subgradient method (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:238:y:2024:i:6:p:1302-1329

DOI: 10.1177/1748006X231196259

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