Data Integrity Attack Detection for Node Voltage in Cyber-Physical Power System

Abstract

In order to accurately detect the false data injection attack for node voltage in the cyber-physical power system, an attack detection method based on recurrent neural network (RNN) is proposed in this paper. The features of voltage data of power topology nodes and the construction method of attack vector are studied. Based on the fast regression algorithm, the best strategy for the data integrity attack of the specific node voltage is solved. The RNN is used to reconstruct time series of the node voltage, and set the threshold of error between the input data and the output data. Then, by calculating whether the error between the reconstructed output data and the original input data exceeds the threshold, it is determined whether the system has suffered data integrity attack. Finally, the feasibility and effectiveness of the detection method proposed in this paper were verified by simulated attack experiments.