Optimal Coding Schemes for Detecting False Data Injection Attacks in Power System State Estimation

As a side-effect-free method, meter coding can successfully detect stealthy false data injection (FDI) attacks without significantly affecting physical plants by encoding the sensor outputs with an invertible matrix. However, since the relationship between the detection of stealthy FDI attacks and the cost of meter coding was not clearly analyzed in existing works, the optimal design of coding schemes has not been well studied. This paper investigates the optimal design of coding schemes based on the analysis of detection conditions for stealthy FDI attacks in power system state estimation. Specifically, detection conditions for stealthy FDI attacks are derived in both general and special coding schemes, which reveal the requirements on the encoded measurements, the coding scheme and the meters in power systems. Utilizing the constraints determined by the detection conditions, the optimization of the special coding scheme is formulated and equivalently simplified, which decouples the design of coding matrix with the other decision variables. Finally, simulation results are carried out on the alternating current (AC) state estimation in the IEEE 14-bus and 57-bus test systems to validate theoretical results on the conditions and cost of detecting stealthy FDI attacks in meter coding.