False data injection attack detection in smart grid based on CNN-BiGRU

Yuan Zeng; Yue Huang; Yaling Chen

doi:10.1117/12.3015826

6 February 2024 False data injection attack detection in smart grid based on CNN-BiGRU

Yuan Zeng, Yue Huang, Yaling Chen

Proceedings Volume 12979, Ninth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023); 1297964 (2024) https://doi.org/10.1117/12.3015826
Event: 9th International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023), 2023, Guilin, China

Abstract

False Data Injection Attacks (FDIAs) are a common security threat to power systems, where an attacker injects false data into the system to interfere with its normal operation. Most of the current research on false data injection attack detection has been conducted in the physical grid environment, while relatively little research has been conducted on new and advanced sensing and measurement technologies to achieve the efficient and smooth operation of smart grids. In this paper, we first provide a comprehensive understanding of FDIAs and investigate the incidents and impacts of FDIA on power systems worldwide. By searching the literature, the existing detection methods for FDIAs are collated, and it is found that most of the existing detection methods use rules or statistical models, which are vulnerable to deception by attackers. Secondly, CNN is used to reduce the dimensionality and extract the spatial features of the high-dimensional measurement information of the power system in the smart grid, and then combined with BiGRU to fully explore the time series features in the information, thus proposing a CNN-BiGRU based detection method of FDIAs in smart grids, and then detecting the measurement information input model of power system and classifying it. This paper also conducts comparison experiments with three commonly used algorithms, CNN, RNN and MLP, and obtains that the research in this paper has high accuracy and certain feasibility.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuan Zeng, Yue Huang, and Yaling Chen "False data injection attack detection in smart grid based on CNN-BiGRU", Proc. SPIE 12979, Ninth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023), 1297964 (6 February 2024); https://doi.org/10.1117/12.3015826

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