Detection of FDI Attacks on Power Grid Using Graph-Theoretical Methods

Smart grid is a reliable and efficient system for electrical power distribution in recent years. One of the drawbacks of this grid is its susceptibility to cyber-attacks. State estimation of the power grid under such an attack is of utmost importance for preventing serious damage to the grid. This paper focuses on the detection of False Data Injection (FDI) attacks that manipulates the Phasor Measurement Unit (PMU) data. An algorithm is presented that can detect the attack zone by analyzing the anomalies in the measurement after the attack. The algorithm is tested on the standard IEEE 118-bus system and the estimation error is used to evaluate the performance of this algorithm. It can successfully detect the attacked buses and estimate the parameters after the attack using graph theoretical methods. The algorithm also differentiates between attacks, load disturbances and single-line faults in the grid.