Research on relay setting attack defense in power systems based on a three-layer optimization model

With the intelligent development of power systems, the number of relays continues to increase. Differences in manufacturers, systems, and protocols lead to growing security risks. Tampering with relay settings could potentially cause power outages or even system instability. Consequently, relay settings have gradually become a key target for cyberattacks, particularly in smart grids where traditional defense measures struggle to effectively address complex and diverse attack scenarios. To address this issue, this paper proposes a three-layer optimization defense model based on game theory, designed to adapt to various attack scenarios. The core methodology of this model includes a three-layer structure: The first layer optimizes the protection level of each relay by allocating limited defense budgets. The second layer analyzes the potential system damage based on the attacker’s strategy choices. The third layer comprehensively calculates system losses to evaluate the effectiveness of defense plans. Through layer-by-layer optimization of budget allocation, the model minimizes the unsupplied energy loss caused by relay setting attacks. Compared to existing methods, this model not only improves defense effectiveness under resource constraints but also addresses multiple complex attack scenarios. Experimental results demonstrate that this model significantly enhances the system’s defense capabilities and effectively reduces the impact of attacks on system security operations.

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Publication Details

Journal
Frontiers in Energy Research
Published
2024-11-21
DOI
https://doi.org/10.3389/fenrg.2024.1502078
Citations
1
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
0.33
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article

Research on relay setting attack defense in power systems based on a three-layer optimization model

Yun Fu, Ren Liu, Junrong Liu, Yihua Zhu et al.
1 citations
Frontiers in Energy Research
Smart Grid Security and Resilience
0.33
article

Research on relay setting attack defense in power systems based on a three-layer optimization model

Yun Fu, Ren Liu, Junrong Liu, Yihua Zhu, Liang Tu, Zeyuan Zhou, Yan Binyuan, Guo Hengdao
article en
1 citations

Abstract

With the intelligent development of power systems, the number of relays continues to increase. Differences in manufacturers, systems, and protocols lead to growing security risks. Tampering with relay settings could potentially cause power outages or even system instability. Consequently, relay settings have gradually become a key target for cyberattacks, particularly in smart grids where traditional defense measures struggle to effectively address complex and diverse attack scenarios. To address this issue, this paper proposes a three-layer optimization defense model based on game theory, designed to adapt to various attack scenarios. The core methodology of this model includes a three-layer structure: The first layer optimizes the protection level of each relay by allocating limited defense budgets. The second layer analyzes the potential system damage based on the attacker’s strategy choices. The third layer comprehensively calculates system losses to evaluate the effectiveness of defense plans. Through layer-by-layer optimization of budget allocation, the model minimizes the unsupplied energy loss caused by relay setting attacks. Compared to existing methods, this model not only improves defense effectiveness under resource constraints but also addresses multiple complex attack scenarios. Experimental results demonstrate that this model significantly enhances the system’s defense capabilities and effectively reduces the impact of attacks on system security operations.

Frontiers in Energy ResearchVol. 12
Guizhou Electric Power Design and Research Institute (CN), China Southern Power Grid (China) (CN)
Openalex Percentile: Top 39%
Smart Grid Security and Resilience
0.33
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Research on relay setting attack defense in power systems based on a three-layer optimization model — Yun Fu, Ren Liu, et al. · Frontiers in Energy Research (2024) | TGRS Research Map | TGRS