Malicious data detection in state estimation leveraging system losses & estimation of perturbed parameters

William Niemira, Rakesh B. Bobba, Peter W Sauer, William H Sanders

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

It is critical that state estimators used in the power grid output accurate results even in the presence of erroneous measurement data. Traditional bad data detection is designed to perform well against isolated random errors. Interacting bad measurements, such as malicious data injection attacks, may be difficult to detect. In this work, we analyze the sensitivities of specific power system quantities to attacks. We compare real and reactive flow and injection measurements as potential indicators of attack. The use of parameter estimation as a means of detecting attack is also investigated. For this the state vector is augmented with known system parameters, allowing both to be estimated simultaneously. Perturbing the system topology is shown to enhance detectability through parameter estimation.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013
Pages402-407
Number of pages6
DOIs
StatePublished - Dec 1 2013
Event2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013 - Vancouver, BC, Canada
Duration: Oct 21 2013Oct 24 2013

Publication series

Name2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013

Other

Other2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013
CountryCanada
CityVancouver, BC
Period10/21/1310/24/13

Fingerprint

State estimation
Parameter estimation
Random errors
Topology

ASJC Scopus subject areas

  • Hardware and Architecture

Cite this

Niemira, W., Bobba, R. B., Sauer, P. W., & Sanders, W. H. (2013). Malicious data detection in state estimation leveraging system losses & estimation of perturbed parameters. In 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013 (pp. 402-407). [6687991] (2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013). https://doi.org/10.1109/SmartGridComm.2013.6687991

Malicious data detection in state estimation leveraging system losses & estimation of perturbed parameters. / Niemira, William; Bobba, Rakesh B.; Sauer, Peter W; Sanders, William H.

2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013. 2013. p. 402-407 6687991 (2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Niemira, W, Bobba, RB, Sauer, PW & Sanders, WH 2013, Malicious data detection in state estimation leveraging system losses & estimation of perturbed parameters. in 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013., 6687991, 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013, pp. 402-407, 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013, Vancouver, BC, Canada, 10/21/13. https://doi.org/10.1109/SmartGridComm.2013.6687991
Niemira W, Bobba RB, Sauer PW, Sanders WH. Malicious data detection in state estimation leveraging system losses & estimation of perturbed parameters. In 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013. 2013. p. 402-407. 6687991. (2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013). https://doi.org/10.1109/SmartGridComm.2013.6687991
Niemira, William ; Bobba, Rakesh B. ; Sauer, Peter W ; Sanders, William H. / Malicious data detection in state estimation leveraging system losses & estimation of perturbed parameters. 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013. 2013. pp. 402-407 (2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013).
@inproceedings{292cf11e1d7441f5a7bace77591152c8,
title = "Malicious data detection in state estimation leveraging system losses & estimation of perturbed parameters",
abstract = "It is critical that state estimators used in the power grid output accurate results even in the presence of erroneous measurement data. Traditional bad data detection is designed to perform well against isolated random errors. Interacting bad measurements, such as malicious data injection attacks, may be difficult to detect. In this work, we analyze the sensitivities of specific power system quantities to attacks. We compare real and reactive flow and injection measurements as potential indicators of attack. The use of parameter estimation as a means of detecting attack is also investigated. For this the state vector is augmented with known system parameters, allowing both to be estimated simultaneously. Perturbing the system topology is shown to enhance detectability through parameter estimation.",
author = "William Niemira and Bobba, {Rakesh B.} and Sauer, {Peter W} and Sanders, {William H}",
year = "2013",
month = "12",
day = "1",
doi = "10.1109/SmartGridComm.2013.6687991",
language = "English (US)",
isbn = "9781479915262",
series = "2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013",
pages = "402--407",
booktitle = "2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013",

}

TY - GEN

T1 - Malicious data detection in state estimation leveraging system losses & estimation of perturbed parameters

AU - Niemira, William

AU - Bobba, Rakesh B.

AU - Sauer, Peter W

AU - Sanders, William H

PY - 2013/12/1

Y1 - 2013/12/1

N2 - It is critical that state estimators used in the power grid output accurate results even in the presence of erroneous measurement data. Traditional bad data detection is designed to perform well against isolated random errors. Interacting bad measurements, such as malicious data injection attacks, may be difficult to detect. In this work, we analyze the sensitivities of specific power system quantities to attacks. We compare real and reactive flow and injection measurements as potential indicators of attack. The use of parameter estimation as a means of detecting attack is also investigated. For this the state vector is augmented with known system parameters, allowing both to be estimated simultaneously. Perturbing the system topology is shown to enhance detectability through parameter estimation.

AB - It is critical that state estimators used in the power grid output accurate results even in the presence of erroneous measurement data. Traditional bad data detection is designed to perform well against isolated random errors. Interacting bad measurements, such as malicious data injection attacks, may be difficult to detect. In this work, we analyze the sensitivities of specific power system quantities to attacks. We compare real and reactive flow and injection measurements as potential indicators of attack. The use of parameter estimation as a means of detecting attack is also investigated. For this the state vector is augmented with known system parameters, allowing both to be estimated simultaneously. Perturbing the system topology is shown to enhance detectability through parameter estimation.

UR - http://www.scopus.com/inward/record.url?scp=84893537671&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84893537671&partnerID=8YFLogxK

U2 - 10.1109/SmartGridComm.2013.6687991

DO - 10.1109/SmartGridComm.2013.6687991

M3 - Conference contribution

AN - SCOPUS:84893537671

SN - 9781479915262

T3 - 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013

SP - 402

EP - 407

BT - 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013

ER -