Real-Time Detection of False Data Injection Attacks in Smart Grid: A Deep Learning-Based Intelligent Mechanism

Application of computing and communications intelligence effectively improves the quality of monitoring and control of smart grids. However, the dependence on information technology also increases vulnerability to malicious attacks. False data injection (FDI), that attack on the integrity of data, is emerging as a severe threat to the supervisory control and data acquisition system. In this paper, we exploit deep learning techniques to recognize the behavior features of FDI attacks with the historical measurement data and employ the captured features to detect the FDI attacks in real-time. By doing so, our proposed detection mechanism effectively relaxes the assumptions on the potential attack scenarios and…