Static Detection of False Data in the Power Grid by Fusing Structure and Attributes of Node

다국어 초록 (Multilingual Abstract)

False data injection attack can evade the traditional state estimation in the power system, resulting in the historical data may have been polluted. Under such circumstances, the contaminated historical data cannot provide the priori data, so data-driven detection cannot be carried out. Hence, this paper proposes a static detection method of false data based on the similarity characteristics of network nodes at a certain time, where structure and attributes of nodes are fused to express nodes based on the egonet model of power grid. In addition, to improve the accuracy of clustering, the detection rate is adopted in the clustering method. The method is tested in IEEE118-bus and 2383-bus systems. The simulation results show that proposed method is effective, and can detect the possible false data injection problems in the power system over 80%.