A Novel Dynamic Watermarking-Based EKF Detection Method for FDIAs in Smart Grid
Xue Li, Ziyi Wang, Changda Zhang, Dajun Du, Minrui Fei
Abstract
Dear editor, The existing bad data detection (BDD) cannot effectively detect false data injection attacks (FDIAs) in smart grid. The objectiveness of this letter is to investigate a novel dynamic watermarking (DW)-based extended Kalman filter (EKF) detection method to detect FDIAs. Firstly, security weakness of traditional <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\chi^{2}$</tex> detector is analyzed, and a novel DW-based EKF detection method is proposed for FDIAs. Secondly, the detection effectiveness and security property of the proposed method are analyzed theoretically, where not only the positive correlation between the detection performance and DW signal intensity but also zero impact of FDIAs not being detected on smart grid (SG) are revealed. Finally, the effectiveness of the proposed method is confirmed by experimental results.