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Minimax-Regret Robust Defensive Strategy Against False Data Injection Attacks

This paper develops a multi-level game-theoretic framework for determining a cost-effective defensive strategy for protecting power systems from false data injection attacks like load redistribution attacks. First, a multi-level optimization problem considering interactions among defenders, attackers and operators is modeled based on the minimax-regret decision rule, which is then reformulated as an equivalent bi-level mixed-integer linear programming problem. Next, an implicit enumeration algorithm is developed to find a globally optimal solution to this complex bi-level problem. Several acceleration techniques are introduced to improve the computation efficiency of the proposed method for large-scale power system applications. Last, the proposed defensive strategy is validated by case studies based on a six-bus test system and a modified two-area RTS-96 system.
- Illinois Institute of Technology United States
- King Abdulaziz University Saudi Arabia
- King Abdulaziz University Saudi Arabia
- Illinois Institute of Technology United States
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).44 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
