On detecting false data injection with limited network information using transformation based statistical techniques

Kush Khanna; Sandeep Kumar Singh; Bijaya Ketan Panigrahi; Ranjan Bose; Anupam Joshi

doi:10.1109/PESGM.2017.8273902

On detecting false data injection with limited network information using transformation based statistical techniques

Kush Khanna, Sandeep Kumar Singh, Bijaya Ketan Panigrahi, Ranjan Bose, Anupam Joshi

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

9 Scopus citations

Abstract

Cyber-attacks poses a serious threat to power system operation. False data injection attack (FDIA) is one such severe threat, if wisely constructed, can cause flawed estimation of power system states, thereby, leading to uneconomical and unsecured operation of power system. In recent years many methods are proposed to secure the smart grid against malicious cyber-events by protecting certain critical measurement sensors. However, making a system completely hack-proof is rather idealistic. In this paper, in addition to the research carried out in this space, we present a new Log transformation based method to detect the FDIA in real time with high probability. The detection probability of the proposed scheme is compared with existing method using IEEE 14 bus system.

Original language	English
Title of host publication	2017 IEEE Power and Energy Society General Meeting, PESGM 2017
Publisher	IEEE Computer Society
Pages	1-5
Number of pages	5
ISBN (Electronic)	9781538622124
DOIs	https://doi.org/10.1109/PESGM.2017.8273902
State	Published - Jan 29 2018
Externally published	Yes
Event	2017 IEEE Power and Energy Society General Meeting, PESGM 2017 - Chicago, United States Duration: Jul 16 2017 → Jul 20 2017

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2018-January
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2017 IEEE Power and Energy Society General Meeting, PESGM 2017
Country/Territory	United States
City	Chicago
Period	07/16/17 → 07/20/17

Keywords

Cyber security
False data injection
Kullback-Leibler distance
Log transformation
Smart grid

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10.1109/PESGM.2017.8273902

Cite this

Khanna, K., Singh, S. K., Panigrahi, B. K., Bose, R., & Joshi, A. (2018). On detecting false data injection with limited network information using transformation based statistical techniques. In 2017 IEEE Power and Energy Society General Meeting, PESGM 2017 (pp. 1-5). (IEEE Power and Energy Society General Meeting; Vol. 2018-January). IEEE Computer Society. https://doi.org/10.1109/PESGM.2017.8273902

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title = "On detecting false data injection with limited network information using transformation based statistical techniques",

abstract = "Cyber-attacks poses a serious threat to power system operation. False data injection attack (FDIA) is one such severe threat, if wisely constructed, can cause flawed estimation of power system states, thereby, leading to uneconomical and unsecured operation of power system. In recent years many methods are proposed to secure the smart grid against malicious cyber-events by protecting certain critical measurement sensors. However, making a system completely hack-proof is rather idealistic. In this paper, in addition to the research carried out in this space, we present a new Log transformation based method to detect the FDIA in real time with high probability. The detection probability of the proposed scheme is compared with existing method using IEEE 14 bus system.",

keywords = "Cyber security, False data injection, Kullback-Leibler distance, Log transformation, Smart grid",

author = "Kush Khanna and Singh, {Sandeep Kumar} and Panigrahi, {Bijaya Ketan} and Ranjan Bose and Anupam Joshi",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE Power and Energy Society General Meeting, PESGM 2017 ; Conference date: 16-07-2017 Through 20-07-2017",

year = "2018",

month = jan,

day = "29",

doi = "10.1109/PESGM.2017.8273902",

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Khanna, K, Singh, SK, Panigrahi, BK, Bose, R & Joshi, A 2018, On detecting false data injection with limited network information using transformation based statistical techniques. in 2017 IEEE Power and Energy Society General Meeting, PESGM 2017. IEEE Power and Energy Society General Meeting, vol. 2018-January, IEEE Computer Society, pp. 1-5, 2017 IEEE Power and Energy Society General Meeting, PESGM 2017, Chicago, United States, 07/16/17. https://doi.org/10.1109/PESGM.2017.8273902

On detecting false data injection with limited network information using transformation based statistical techniques. / Khanna, Kush; Singh, Sandeep Kumar; Panigrahi, Bijaya Ketan et al.
2017 IEEE Power and Energy Society General Meeting, PESGM 2017. IEEE Computer Society, 2018. p. 1-5 (IEEE Power and Energy Society General Meeting; Vol. 2018-January).

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

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AB - Cyber-attacks poses a serious threat to power system operation. False data injection attack (FDIA) is one such severe threat, if wisely constructed, can cause flawed estimation of power system states, thereby, leading to uneconomical and unsecured operation of power system. In recent years many methods are proposed to secure the smart grid against malicious cyber-events by protecting certain critical measurement sensors. However, making a system completely hack-proof is rather idealistic. In this paper, in addition to the research carried out in this space, we present a new Log transformation based method to detect the FDIA in real time with high probability. The detection probability of the proposed scheme is compared with existing method using IEEE 14 bus system.

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KW - Kullback-Leibler distance

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KW - Smart grid

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On detecting false data injection with limited network information using transformation based statistical techniques

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