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

Zhengwei Qu,Yunjing Wang,Jingchuan Yang,Xiaoming Han,Xinyue Guo,Yansheng Lang

doi:10.3390/en15051733

Zhengwei Qu, Yunjing Wang + Show 4 more

Open Access

https://doi.org/10.3390/en15051733

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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.

Highlights

In recent years, sensing, communication, and control technologies have been able to realize the seamless integration in smart grids
At the same time, when injecting false data that can evade bad data detections (BDDs), the Earth-Mover Distance (EMD) range is shifted to the right, and the offset of the EMD range increases as the attack intensity increases
False data injection attacks (FDIAs) pose a great threat to power grid operation

Summary

Introduction

In recent years, sensing, communication, and control technologies have been able to realize the seamless integration in smart grids. After collecting measurement data through remote terminal units (RTUs), the smart grid relies on the state estimation algorithm to achieve its regulation. False data injection attacks (FDIAs), as a covert cyber-attack method, pose a huge challenge to the safe and stable operation of smart grids by illegally hacking into power systems to tamper with measurement data and undermine data integrity [3,4,5]. In [6], Liu et al first proposed the concept of FDIAs and mentioned that attackers can use power system topology and parameter information to construct a well- designed attack vector that bypasses traditional bad data detections (BDDs) and destroys the integrity of smart grid information.

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Conclusion