Comparative Study of False Data Injection Attack Detection Techniques in AC Smart Island

Power distribution operators are enhancing the monitoring and control of the whole power system accurately and effectively using real time measurement data from the sophisticated metering infrastructure in Smart Island (SI). False data injection attack (FDIA), which is considered as sophisticated information security attack, targets components, such as controllers, sensors, and remote Phasor measurement unit (PMU), and impacts the system's operational decisions. To effectively link FDIAs to network safety, it is necessary to conduct more comprehensive investigations into power systems. A potential approach for detecting cyber-attacks on the system using non-stationary signal analysis involves utilizing a time-frequency-based differential technique. In this paper, bad data detection methods in AC- Smart Island using the Hilbert Huang Transform (HHT) technique and Wavelet Singular Entropy (WSE) technique are studied. HHT is based on a non-stationary signal processing approach implemented for false data injection into the system. The paper demonstrates the comparative analysis between HHT and WSE based FDIA detection techniques using MATLAB program.