Hidden Attacks on Power Grid: Optimal Attack Strategies and Mitigation
This addresses security vulnerabilities in power grid operations, which can prevent costly errors like electricity price increases or line outages, though it is incremental as it builds on existing attack and mitigation strategies.
The paper tackles hidden data attacks on power grid state estimation by developing a polynomial-time algorithm to find the minimum number of meters an adversary must manipulate, and it presents greedy techniques for operators to protect critical measurements, with simulations on IEEE test cases demonstrating performance.
Real time operation of the power grid and synchronism of its different elements require accurate estimation of its state variables. Errors in state estimation will lead to sub-optimal Optimal Power Flow (OPF) solutions and subsequent increase in the price of electricity in the market or, potentially overload and create line outages. This paper studies hidden data attacks on power systems by an adversary trying to manipulate state estimators. The adversary gains control of a few meters, and is able to introduce spurious measurements in them. The paper presents a polynomial time algorithm using min-cut calculations to determine the minimum number of measurements an adversary needs to manipulate in order to perform a hidden attack. Greedy techniques are presented to aid the system operator in identifying critical measurements for protection to prevent such hidden data attacks. Secure PMU placement against data attacks is also discussed and an algorithm for placing PMUs for this purpose is developed. The performances of the proposed algorithms are shown through simulations on IEEE test cases.