Weibull Distribution based False Data Injection Attack Detection

Abstract

False Data Injection (FDI) attack can lead to incorrect state estimation (SE) at control center, thereby giving incorrect information about the system operation. Therefore, the detection of FDI attacks on measurements is crucial. This paper proposes a methodology based on the Weibull Distribution (WD) to detect FDI attacks on single or multiple measurements received from Phasor Measurement Units (PMUs) and Supervisory Control and Data Acquisition (SCADA) system. The Weibull Cumulative Distribution Function (CDF) with two parameters, scale and shape, has been used in this paper. The proposed method estimates the shape parameter of CDF for each measurement by taking a small measurement window. The presence of attack in a measurement window is detected by comparing the shape parameter with a specified threshold value. The performance of the proposed method is validated on the measurements generated for the IEEE 14-bus system using the Real-Time Digital Simulator (RTDS). Furthermore, the proposed method has been validated at various attack magnitudes along with different probability of attack on measurements. © 2024 IEEE.