Online Robust PCA for Malicious Attack-Resilience in Wide-Area Mode Metering Application

Kaveri Mahapatra; Nilanjan Ray Chaudhuri

doi:10.1109/TPWRS.2019.2895301

Online Robust PCA for Malicious Attack-Resilience in Wide-Area Mode Metering Application

Kaveri Mahapatra, Nilanjan Ray Chaudhuri

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21 Scopus citations

Abstract

This paper presents a method for detecting and correcting malicious data corruptions in phasor measurement unit (PMU) measurements. Detection of malicious injections is formulated as a compressed sensing problem and the actual signals are recovered using an online robust principal component analysis-based algorithm. Different patterns of malicious injection attacks on PMU data are considered and the effect of corruption and reconstruction using the algorithm is analyzed on a wide-area mode metering application. The performance of the proposed algorithm has been evaluated with different subspace selection. A suitable threshold for the algorithm is selected by a graphical analysis of the receiver operating characteristics curve. Data from a 16-machine, 5-area New England-New York system is used along with a recursive modal estimation algorithm to validate the effectiveness of the proposed approach under ambient and transient conditions.

Original language	English (US)
Article number	8626487
Pages (from-to)	2598-2610
Number of pages	13
Journal	IEEE Transactions on Power Systems
Volume	34
Issue number	4
DOIs	https://doi.org/10.1109/TPWRS.2019.2895301
State	Published - Jul 2019

All Science Journal Classification (ASJC) codes

Energy Engineering and Power Technology
Electrical and Electronic Engineering

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10.1109/TPWRS.2019.2895301

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title = "Online Robust PCA for Malicious Attack-Resilience in Wide-Area Mode Metering Application",

abstract = "This paper presents a method for detecting and correcting malicious data corruptions in phasor measurement unit (PMU) measurements. Detection of malicious injections is formulated as a compressed sensing problem and the actual signals are recovered using an online robust principal component analysis-based algorithm. Different patterns of malicious injection attacks on PMU data are considered and the effect of corruption and reconstruction using the algorithm is analyzed on a wide-area mode metering application. The performance of the proposed algorithm has been evaluated with different subspace selection. A suitable threshold for the algorithm is selected by a graphical analysis of the receiver operating characteristics curve. Data from a 16-machine, 5-area New England-New York system is used along with a recursive modal estimation algorithm to validate the effectiveness of the proposed approach under ambient and transient conditions.",

author = "Kaveri Mahapatra and Chaudhuri, {Nilanjan Ray}",

note = "Funding Information: Manuscript received March 2, 2018; revised September 10, 2018 and December 10, 2018; accepted January 18, 2019. Date of publication January 25, 2019; date of current version June 18, 2019. This work was supported by the NSF under Grants CNS 1544621 and CNS 1739206. Paper no. TPWRS-00312-2018. (Corresponding author: Nilanjan Ray Chaudhuri.) The authors are with the School of Electrical Engineering and Computer Science, The Pennsylvania State University, State College, PA 16802 USA (e-mail:,kzm221@psu.edu; nuc88@engr.psu.edu). Funding Information: This work was supported by the NSF under Grants CNS 1544621 and CNS 1739206. Paper no. TPWRS-00312-2018. Publisher Copyright: {\textcopyright} 1969-2012 IEEE.",

year = "2019",

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AU - Chaudhuri, Nilanjan Ray

N1 - Funding Information: Manuscript received March 2, 2018; revised September 10, 2018 and December 10, 2018; accepted January 18, 2019. Date of publication January 25, 2019; date of current version June 18, 2019. This work was supported by the NSF under Grants CNS 1544621 and CNS 1739206. Paper no. TPWRS-00312-2018. (Corresponding author: Nilanjan Ray Chaudhuri.) The authors are with the School of Electrical Engineering and Computer Science, The Pennsylvania State University, State College, PA 16802 USA (e-mail:,kzm221@psu.edu; nuc88@engr.psu.edu). Funding Information: This work was supported by the NSF under Grants CNS 1544621 and CNS 1739206. Paper no. TPWRS-00312-2018. Publisher Copyright: © 1969-2012 IEEE.

PY - 2019/7

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N2 - This paper presents a method for detecting and correcting malicious data corruptions in phasor measurement unit (PMU) measurements. Detection of malicious injections is formulated as a compressed sensing problem and the actual signals are recovered using an online robust principal component analysis-based algorithm. Different patterns of malicious injection attacks on PMU data are considered and the effect of corruption and reconstruction using the algorithm is analyzed on a wide-area mode metering application. The performance of the proposed algorithm has been evaluated with different subspace selection. A suitable threshold for the algorithm is selected by a graphical analysis of the receiver operating characteristics curve. Data from a 16-machine, 5-area New England-New York system is used along with a recursive modal estimation algorithm to validate the effectiveness of the proposed approach under ambient and transient conditions.

AB - This paper presents a method for detecting and correcting malicious data corruptions in phasor measurement unit (PMU) measurements. Detection of malicious injections is formulated as a compressed sensing problem and the actual signals are recovered using an online robust principal component analysis-based algorithm. Different patterns of malicious injection attacks on PMU data are considered and the effect of corruption and reconstruction using the algorithm is analyzed on a wide-area mode metering application. The performance of the proposed algorithm has been evaluated with different subspace selection. A suitable threshold for the algorithm is selected by a graphical analysis of the receiver operating characteristics curve. Data from a 16-machine, 5-area New England-New York system is used along with a recursive modal estimation algorithm to validate the effectiveness of the proposed approach under ambient and transient conditions.

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Online Robust PCA for Malicious Attack-Resilience in Wide-Area Mode Metering Application

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