Detection of False Data Injection Attacks in AC State Estimation Using Phasor Measurements
Zhenhua Wang, Haibo He, Zhiqiang Wan, Yan Sun
Abstract
This paper investigates the detection of False Data Injection Attacks (FDIAs) in AC state estimation where attackers cannot obtain the accurate transmission line admittances and the accurate estimated system state variables. Unlike previous works that assume attackers can get accurate values, the scenario studied in this paper represents a more practical and generalized situation. Sufficient conditions for launching FDIAs without being detected by the traditional residual-based bad data detector are derived. In order to detect these FDIAs effectively, a robust detection method using secure PMU measured data is proposed. In the proposed detection method, secure PMU measured data and the Bisquare estimator are used to estimate system state variables. Then, the expected SCADA measurements are calculated based on these estimated state variables. Finally, the statistical consistency between the received SCADA measurements and the expected SCADA measurements is utilized to detect FDIAs. Simulations on the IEEE 30-bus, IEEE 118-bus, and IEEE 300-bus systems are conducted to verify the effectiveness of the proposed robust detection method.