Detection and isolation of false data injection attack via adaptive Kalman filter bank  

作　　者：Xiaoyuan Luo Minggao Zhu Xinyu Wang Xinping Guan 

机构地区：[1]School of Electrical Engineering,Yanshan University,Qinhuangdao,People’s Republic of China [2]Jiangsu Collaborative Innovation Center for Smart Distribution Network,Nanjing,People’s Republic of China [3]School of Electronic,Information and Electrical Engineering,Shanghai Jiao Tong University,Shanghai,People’s Republic of China

出　　处：《Journal of Control and Decision》2024年第1期60-72,共13页控制与决策学报（英文）

基　　金：the National Nature Science Foundation of China under 61873228 and 62103357;the Science and Technology Plan of Hebei Education Department under QN2021139;the Nature Science Foundation of Hebei Province under F2021203043;the Open Research Fund of Jiangsu Collaborative Innovation Center for Smart Distribution Network,Nanjing Institute of Technology under XTCX202203.

摘　　要：Due to the integration of cyber–physical systems,smart grids have faced the new security risks caused by false data injection attacks(FDIAs).FDIAs can bypass the traditional bad data detection techniques by falsifying the process of state estimation.For this reason,this paper studies the detection and isolation problem of FDIAs based on the adaptive Kalman filter bank(AKFB)in smart grids.Taking the covert characteristics of FDIAs into account,a novel detection method is proposed based on the designed AKF.Moreover,the adaptive threshold is proposed to solve the detection delay caused by a priori threshold in the current detection methods.Considering the case of multiple attacked sensor nodes,the AKFB-based isolation method is developed.To reduce the number of isolation iterations,a logical decision matrix scheme is designed.Finally,the effectiveness of the proposed detection and isolation method is demonstrated on an IEEE 22-bus smart grids.

关 键 词：Smart grids false data inject attack detection and isolation Kalman filter bank 

分 类 号：TN713[电子电信—电路与系统]