Tong Zu, Fengyong Li*
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1395-1417, 2024, DOI:10.32604/cmes.2024.055442
Abstract False data injection attack (FDIA) can affect the state estimation of the power grid by tampering with the measured value of the power grid data, and then destroying the stable operation of the smart grid. Existing work usually trains a detection model by fusing the data-driven features from diverse power data streams. Data-driven features, however, cannot effectively capture the differences between noisy data and attack samples. As a result, slight noise disturbances in the power grid may cause a large number of false detections for FDIA attacks. To address this problem, this paper designs a… More >
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