False Data Injection Detection for Phasor Measurement Units
Saleh Almasabi,
Turki Alsuwian,
Muhammad Awais,
Muhammad Irfan,
Mohammed Jalalah,
Belqasem Aljafari,
Farid A. Harraz
Affiliations
Saleh Almasabi
Electrical Engineering Department, College of Engineering, Najran University, Najran 11001, Saudi Arabia
Turki Alsuwian
Electrical Engineering Department, College of Engineering, Najran University, Najran 11001, Saudi Arabia
Muhammad Awais
Department of Computer Science, Edge Hill University, Ormskirk L39 4QP, UK
Muhammad Irfan
Electrical Engineering Department, College of Engineering, Najran University, Najran 11001, Saudi Arabia
Mohammed Jalalah
Electrical Engineering Department, College of Engineering, Najran University, Najran 11001, Saudi Arabia
Belqasem Aljafari
Electrical Engineering Department, College of Engineering, Najran University, Najran 11001, Saudi Arabia
Farid A. Harraz
Promising Centre for Sensors and Electronic Devices (PCSED), Advanced Materials and Nano-Research Centre, Najran University, P.O. Box 1988, Najran 11001, Saudi Arabia
Cyber-threats are becoming a big concern due to the potential severe consequences of such threats is false data injection (FDI) attacks where the measures data is manipulated such that the detection is unfeasible using traditional approaches. This work focuses on detecting FDIs for phasor measurement units where compromising one unit is sufficient for launching such attacks. In the proposed approach, moving averages and correlation are used along with machine learning algorithms to detect such attacks. The proposed approach is tested and validated using the IEEE 14-bus and the IEEE 30-bus test systems. The proposed performance was sufficient for detecting the location and attack instances under different scenarios and circumstances.
