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Title: Low Latency Detection of Sparse False Data Injections in Smart Grids

Abstract

We study low-latency detections of sparse false data injection attacks in power grids, where an adversary can maliciously manipulate power grid operations by modifying measurements at a small number of smart meters. When a power grid is under attack, the detection delay, which is defined as the time difference between the occurrence and detection of the attack, is critical to power grid operations. A shorter detection delay can shorten the response time, thus prevent catastrophic impacts from the attack. The objective of this paper is to develop low-latency false data detection algorithms that can minimize the detection delay subject to constraints on false alarm probability. The false data injection can be modeled with a sparse attack vector, with each non-zero element corresponding to one meter under attack. Since neither the support nor the values of the sparse attack vector is known, a new orthogonal matching pursuit cumulative sum (OMP-CUSUM) algorithm is proposed to identify the meters under attack while minimizing the detection delay. In order to recover the support of the sparse vector, we develop a new stopping condition for the iterative OMP algorithm by analyzing the statistical properties of the power grid measurements. Theoretical analysis and simulation results showmore » that the proposed OMP-CUSUM algorithm can efficiently identify the meters under attack, and reliably detect false data injections with low delays while maintaining good detection accuracy.« less

Authors:
; ORCiD logo
Publication Date:
Research Org.:
Univ. of Arkansas, Little Rock, AR (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1482403
Alternate Identifier(s):
OSTI ID: 1482404; OSTI ID: 1511445
Grant/Contract Number:  
OE0000779; ECCS-1405403; ECCS-1711087
Resource Type:
Published Article
Journal Name:
IEEE Access
Additional Journal Information:
Journal Name: IEEE Access Journal Volume: 6; Journal ID: ISSN 2169-3536
Publisher:
Institute of Electrical and Electronics Engineers
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; Low latency detection; orthogonal matching pursuit; false data injection; cumulative sum

Citation Formats

Akingeneye, Israel, and Wu, Jingxian. Low Latency Detection of Sparse False Data Injections in Smart Grids. United States: N. p., 2018. Web. doi:10.1109/ACCESS.2018.2873981.
Akingeneye, Israel, & Wu, Jingxian. Low Latency Detection of Sparse False Data Injections in Smart Grids. United States. doi:10.1109/ACCESS.2018.2873981.
Akingeneye, Israel, and Wu, Jingxian. Mon . "Low Latency Detection of Sparse False Data Injections in Smart Grids". United States. doi:10.1109/ACCESS.2018.2873981.
@article{osti_1482403,
title = {Low Latency Detection of Sparse False Data Injections in Smart Grids},
author = {Akingeneye, Israel and Wu, Jingxian},
abstractNote = {We study low-latency detections of sparse false data injection attacks in power grids, where an adversary can maliciously manipulate power grid operations by modifying measurements at a small number of smart meters. When a power grid is under attack, the detection delay, which is defined as the time difference between the occurrence and detection of the attack, is critical to power grid operations. A shorter detection delay can shorten the response time, thus prevent catastrophic impacts from the attack. The objective of this paper is to develop low-latency false data detection algorithms that can minimize the detection delay subject to constraints on false alarm probability. The false data injection can be modeled with a sparse attack vector, with each non-zero element corresponding to one meter under attack. Since neither the support nor the values of the sparse attack vector is known, a new orthogonal matching pursuit cumulative sum (OMP-CUSUM) algorithm is proposed to identify the meters under attack while minimizing the detection delay. In order to recover the support of the sparse vector, we develop a new stopping condition for the iterative OMP algorithm by analyzing the statistical properties of the power grid measurements. Theoretical analysis and simulation results show that the proposed OMP-CUSUM algorithm can efficiently identify the meters under attack, and reliably detect false data injections with low delays while maintaining good detection accuracy.},
doi = {10.1109/ACCESS.2018.2873981},
journal = {IEEE Access},
number = ,
volume = 6,
place = {United States},
year = {2018},
month = {1}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1109/ACCESS.2018.2873981

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