Detection of False Data Injection Attacks in Smart Grids: A Real-Time Principle Component Analysis

False Data Injection (FDI) is one of the most dangerous attacks on cyber-physical systems as it could lead to disastrous consequences in the operation of the power grids. In this paper, a comprehensive investigation of the (FDI) attacks in smart grids is presented. A detection algorithm is utilized in analyzing the FDI attacks in real-time environment based on Principle Component Analysis (PCA). It provides an adequate solution to the FDI problem for its ability to extract information about correlation of the collected measurements. This provides a more accurate and sensitive response than the previous FDI detection techniques. Furthermore, the light computations associated with this algorithm make it a very good candidate for real-time environment testing. The results concluded in the paper illustrate a very promising future for the PCA-based realtime FDI attack detection schemes.

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