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Joint transformation based detection of false data injection attacks in smart grid

Authors: Sandeep Kumar Singh, Kush Khanna, Ranjan Bose, and Anupam Joshi

Journal: IEEE Transactions on Industrial Informatics

Date: June 28, 2017

Abstract: For reliable operation and control of smart grid, estimating the correct states is of utmost importance to the system operator. With recent incorporation of information technology and Advanced Metering Infrastructure (AMI), the futuristic grid is more prone to cyber-threats. The False Data Injection (FDI) attack is one of the most thoroughly researched cyber-attacks. Intelligently crafted, it can cause false estimation of states, which further seriously affects the entire power system operation. In this paper, we propose Joint Transformation based scheme to detect FDI attacks in real time. The proposed method is built on the dynamics of measurement variations. Kullback-Leibler Distance (KLD) is used to find out the difference between probability distributions obtained from measurement variations. The proposed method is tested using IEEE 14 bus system considering attack on different state variables. The results shows that the proposed scheme detects FDI attacks with high detection probability.

Type: Article

Tags: smart grids, transmission line measurements, state estimation, probability distribution, real-time systems, meters

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