A Game-Theoretic Approach for PMU Deployment Against False Data Injection Attacks
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866914760239349760 |
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| author | Maleki, Sajjad Lakshminarayana, Subhash Belmega, E. Veronica Maple, Carsten |
| author_facet | Maleki, Sajjad Lakshminarayana, Subhash Belmega, E. Veronica Maple, Carsten |
| contents | Phasor Measurement Units (PMUs) are used in the measurement, control and protection of power grids. However, deploying PMUs at every bus in a power system is prohibitively expensive, necessitating partial PMU placement that can ensure system observability with minimal units. One consequence of this economic approach is increased system vulnerability to False Data Injection Attacks (FDIAs). This paper proposes a zero-sum game-based approach to strategically place an additional PMU (following the initial optimal PMU deployment that ensures full observability) to bolster robustness against FDIAs by introducing redundancy in attack-susceptible areas. To compute the Nash equilibrium (NE) solution, we leverage a reinforcement learning algorithm that mitigates the need for complete knowledge of the opponent's actions. The proposed PMU deployment algorithm increases the detection rate of FDIA by 36% compared to benchmark algorithms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_10520 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Game-Theoretic Approach for PMU Deployment Against False Data Injection Attacks Maleki, Sajjad Lakshminarayana, Subhash Belmega, E. Veronica Maple, Carsten Systems and Control Phasor Measurement Units (PMUs) are used in the measurement, control and protection of power grids. However, deploying PMUs at every bus in a power system is prohibitively expensive, necessitating partial PMU placement that can ensure system observability with minimal units. One consequence of this economic approach is increased system vulnerability to False Data Injection Attacks (FDIAs). This paper proposes a zero-sum game-based approach to strategically place an additional PMU (following the initial optimal PMU deployment that ensures full observability) to bolster robustness against FDIAs by introducing redundancy in attack-susceptible areas. To compute the Nash equilibrium (NE) solution, we leverage a reinforcement learning algorithm that mitigates the need for complete knowledge of the opponent's actions. The proposed PMU deployment algorithm increases the detection rate of FDIA by 36% compared to benchmark algorithms. |
| title | A Game-Theoretic Approach for PMU Deployment Against False Data Injection Attacks |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2404.10520 |