Quickest Detection of False Data Injection Attack in Wide-Area Smart Grids

We consider the sequential (i.e., online) detection of false data injection attacks in smart grid, which aims to manipulate the state estimation procedure by injecting malicious data to the monitoring meters. The unknown parameters in the system, namely the state vector, injected malicious data and...

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Vydáno v:IEEE transactions on smart grid Ročník 6; číslo 6; s. 2725 - 2735
Hlavní autoři: Li, Shang, Yilmaz, Yasin, Wang, Xiaodong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.11.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Cyber security
Detectors
distributed algorithm
Distributed algorithms
generalized CUSUM
level-triggered sampling
Monitoring
Power system security
Robustness
Sensors
smart grid quickest detection
wide-area monitoring
distributed algorithm
wide-area monitoring
Cyber security
smart grid quickest detection
generalized CUSUM
level-triggered sampling
ISSN:1949-3053, 1949-3061
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Shrnutí:We consider the sequential (i.e., online) detection of false data injection attacks in smart grid, which aims to manipulate the state estimation procedure by injecting malicious data to the monitoring meters. The unknown parameters in the system, namely the state vector, injected malicious data and the set of attacked meters pose a significant challenge for designing a robust, computationally efficient, and high-performance detector. We propose a sequential detector based on the generalized likelihood ratio to address this challenge. Specifically, the proposed detector is designed to be robust to a variety of attacking strategies, and load situations in the power system, and its computational complexity linearly scales with the number of meters. Moreover, it considerably outperforms the existing first-order cumulative sum detector in terms of the average detection delay and robustness to various attacking strategies. For wide-area monitoring in smart grid, we further develop a distributed sequential detector using an adaptive sampling technique called level-triggered sampling. The resulting distributed detector features single bit per sample in terms of the communication overhead, while preserving the high performance of the proposed centralized detector.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2014.2374577