Earth-Mover-Distance-Based Detection of False Data Injection Attacks in Smart Grids

Zhengwei Qu, Jingchuan Yang, Yansheng Lang, Yunjing Wang, Xiaoming Han and Xinyue Guo
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Zhengwei Qu: State Key Laboratory of Power Grid Safety and Energy Conservation, China Electric Power Research Institute, Beijing 100192, China
Jingchuan Yang: School of Electrical Engineering, Yanshan University, Qinghuangdao 066004, China
Yansheng Lang: State Key Laboratory of Power Grid Safety and Energy Conservation, China Electric Power Research Institute, Beijing 100192, China
Yunjing Wang: School of Electrical Engineering, Yanshan University, Qinghuangdao 066004, China
Xiaoming Han: School of Electrical Engineering, Yanshan University, Qinghuangdao 066004, China
Xinyue Guo: School of Electrical Engineering, Yanshan University, Qinghuangdao 066004, China

Energies, 2022, vol. 15, issue 5, 1-16

Abstract: The high integration of power information physical system improves the efficiency of power transmission, but it also brings new threats to power grid. False data injection attacks can use traditional bad data to detect vulnerabilities and maliciously tamper with measurement data to affect the state estimation results. In order to achieve a higher security level for power systems, we propose an earth mover distance method to detect false data injection attacks in smart grids. The proposed method is built on the dynamic correlation of measurement data between adjacent moments. Firstly, a joint-image-transformation-based scheme is proposed to preprocess the measurement data variation, so that the distribution characteristics of measurement data variation are more significant. Secondly, the deviation between the probability distribution of measurement data variation and the histogram are obtained based on the earth’s mover distance. Finally, a reasonable detection threshold is selected to judge whether there are false data injection attacks. The proposed method is tested using IEEE 14 bus system considering the state variable attacks on different nodes. The results verified that the proposed method has a high detection accuracy against false data injection attacks.

Keywords: earth’s mover distance (EMD); false data injection attacks (FDIAs); joint image transformation (JIT); smart grid (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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