@inproceedings{95cda915248843fb85600b3bd8667ff6,
title = "Detection of False Data Injection Attacks in Smart Grids: A Real-Time Principle Component Analysis",
abstract = "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.",
keywords = "cyber security, Cyber-physical systems, false data injection attack (FDIA), phasor measurement units (PMU), principle component analysis (PCA), real-time implementation, smart grid",
author = "Musleh, \{Ahmed S.\} and Mahdi Debouza and Khalid, \{Haris M.\} and Ahmed Al-Durra",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019 ; Conference date: 14-10-2019 Through 17-10-2019",
year = "2019",
month = oct,
doi = "10.1109/IECON.2019.8927453",
language = "British English",
series = "IECON Proceedings (Industrial Electronics Conference)",
publisher = "IEEE Computer Society",
pages = "2958--2963",
booktitle = "Proceedings",
address = "United States",
}
