LAUSR

Wind farm industrial control systems (ICSs) play an important role in the operation of wind turbines (WTs). To increase revenues, a corrupt wind power producer tends to compromise the ICSs of the opponents’ wind farms by launching false data injection (FDI) attacks. In this article, we investigate a novel profit-oriented FDI (POFDI) attack against wind farms and study corresponding attack detection schemes. Specifically, we proposed a potential FDI attack model against ICSs of wind farms considering the power distribution of wind farms. Based on the characteristics of the proposed attack model, a profit-oriented attack strategy is discussed as a composition of attack detection. Considering the characteristics of the compromised data and those of normal data, we develop countermeasures to detect the POFDI attack, through the relationship between the characteristics of WTs in wind farms. A relation-based detection network is used to evaluate the similarity between the data to be tested and the historical data. Simulation results show the impact of the proposed attack strategy and the effectiveness of the attack detection scheme.