A polynomial-time method to find the sparsest unobservable attacks in power networks

Yue Zhao; Andrea Goldsmith; H. Vincent Poor

doi:10.1109/ACC.2016.7524928

A polynomial-time method to find the sparsest unobservable attacks in power networks

Yue Zhao
, Andrea Goldsmith
, H. Vincent Poor

Princeton University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Power injection attacks that alter generation and loads at buses in power networks are studied. The system operator employs Phasor Measurement Units (PMUs) to detect such physical attacks, while attackers devise attacks that are unobservable by such PMU networks. Unalterable buses, whose power injections cannot be changed, are also considered in our model. It is shown that, given the PMU locations, the minimum sparsity of unobservable attacks has a simple form with probability one, namely, equation, where equation is defined as the vulnerable vertex connectivity of an augmented graph. The constructive proof allows one to find the entire set of the sparsest unobservable attacks in polynomial time.

Original language	English
Title of host publication	2016 American Control Conference, ACC 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	276-282
Number of pages	7
ISBN (Electronic)	9781467386821
DOIs	https://doi.org/10.1109/ACC.2016.7524928
State	Published - Jul 28 2016
Event	2016 American Control Conference, ACC 2016 - Boston, United States Duration: Jul 6 2016 → Jul 8 2016

Publication series

Name	Proceedings of the American Control Conference
Volume	2016-July
ISSN (Print)	0743-1619

Conference

Conference	2016 American Control Conference, ACC 2016
Country/Territory	United States
City	Boston
Period	07/6/16 → 07/8/16

Access to Document

10.1109/ACC.2016.7524928

Cite this

Zhao, Y., Goldsmith, A., & Poor, H. V. (2016). A polynomial-time method to find the sparsest unobservable attacks in power networks. In 2016 American Control Conference, ACC 2016 (pp. 276-282). Article 7524928 (Proceedings of the American Control Conference; Vol. 2016-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2016.7524928

@inproceedings{9888e4eb540440e19be224b47f5bb3b9,

title = "A polynomial-time method to find the sparsest unobservable attacks in power networks",

abstract = "Power injection attacks that alter generation and loads at buses in power networks are studied. The system operator employs Phasor Measurement Units (PMUs) to detect such physical attacks, while attackers devise attacks that are unobservable by such PMU networks. Unalterable buses, whose power injections cannot be changed, are also considered in our model. It is shown that, given the PMU locations, the minimum sparsity of unobservable attacks has a simple form with probability one, namely, equation, where equation is defined as the vulnerable vertex connectivity of an augmented graph. The constructive proof allows one to find the entire set of the sparsest unobservable attacks in polynomial time.",

author = "Yue Zhao and Andrea Goldsmith and Poor, \{H. Vincent\}",

note = "Publisher Copyright: {\"i}¿½ 2016 American Automatic Control Council (AACC).; 2016 American Control Conference, ACC 2016 ; Conference date: 06-07-2016 Through 08-07-2016",

year = "2016",

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doi = "10.1109/ACC.2016.7524928",

language = "English",

series = "Proceedings of the American Control Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Zhao, Y , Goldsmith, A & Poor, HV 2016, A polynomial-time method to find the sparsest unobservable attacks in power networks. in 2016 American Control Conference, ACC 2016., 7524928, Proceedings of the American Control Conference, vol. 2016-July, Institute of Electrical and Electronics Engineers Inc., pp. 276-282, 2016 American Control Conference, ACC 2016, Boston, United States, 07/6/16. https://doi.org/10.1109/ACC.2016.7524928

A polynomial-time method to find the sparsest unobservable attacks in power networks. / Zhao, Yue ; Goldsmith, Andrea; Poor, H. Vincent.
2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 276-282 7524928 (Proceedings of the American Control Conference; Vol. 2016-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Goldsmith, Andrea

AU - Poor, H. Vincent

PY - 2016/7/28

Y1 - 2016/7/28

N2 - Power injection attacks that alter generation and loads at buses in power networks are studied. The system operator employs Phasor Measurement Units (PMUs) to detect such physical attacks, while attackers devise attacks that are unobservable by such PMU networks. Unalterable buses, whose power injections cannot be changed, are also considered in our model. It is shown that, given the PMU locations, the minimum sparsity of unobservable attacks has a simple form with probability one, namely, equation, where equation is defined as the vulnerable vertex connectivity of an augmented graph. The constructive proof allows one to find the entire set of the sparsest unobservable attacks in polynomial time.

AB - Power injection attacks that alter generation and loads at buses in power networks are studied. The system operator employs Phasor Measurement Units (PMUs) to detect such physical attacks, while attackers devise attacks that are unobservable by such PMU networks. Unalterable buses, whose power injections cannot be changed, are also considered in our model. It is shown that, given the PMU locations, the minimum sparsity of unobservable attacks has a simple form with probability one, namely, equation, where equation is defined as the vulnerable vertex connectivity of an augmented graph. The constructive proof allows one to find the entire set of the sparsest unobservable attacks in polynomial time.

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BT - 2016 American Control Conference, ACC 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 American Control Conference, ACC 2016

Y2 - 6 July 2016 through 8 July 2016

ER -

A polynomial-time method to find the sparsest unobservable attacks in power networks

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