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Title: Spatio-Temporal Characterization of Synchrophasor Data Against Spoofing Attacks in Smart Grids

Abstract

“Source ID Mix” has emerged as a new type of highly deceiving attack which can alter the source information of synchrophasor data measured by multiple phasor measurement units, thereby paralyzing many wide-area measurement systems applications. To address such sophisticated cyber attacks, we have exploited the spatio-temporal characteristics of synchrophasor data for authenticating measurements’ source information. Specifically, the source authentication is performed when the measurements are subjected to three types of spoofing attacks. Some practical difficulties in applying the proposed method on real-time authentication caused by insufficient measurement data have also been solved. Experimental results with real synchrophasor measurements have validated the effectiveness of the proposed method in detecting such complicated data spoofing and improving power systems’ cyber security.

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1];  [2];  [2]
  1. Univ. of Tennessee, Knoxville, TN (United States). Dept. of Electrical Engineering and Computer Science
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1564165
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
IEEE Transactions on Smart Grid
Additional Journal Information:
Journal Volume: 10; Journal Issue: 5; Journal ID: ISSN 1949-3053
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; Frequency control; Authentication; Time-frequency analysis; Power measurement; Frequency estimation; authorisation; power engineering computing; power system security; smart power grids; spatio-temporal characteristics; source authentication; real-time authentication; synchrophasor measurements; Source ID Mix; cyber attacks; Cyber security; machine learning; phasor measurement unit (PMU); spoofing attack; wide-area measurement systems (WAMS)

Citation Formats

Cui, Yi, Bai, Feifei, Liu, Yilu, Fuhr, Peter L., and Morales-Rodriguez, Marissa E. Spatio-Temporal Characterization of Synchrophasor Data Against Spoofing Attacks in Smart Grids. United States: N. p., 2019. Web. doi:10.1109/TSG.2019.2891852.
Cui, Yi, Bai, Feifei, Liu, Yilu, Fuhr, Peter L., & Morales-Rodriguez, Marissa E. Spatio-Temporal Characterization of Synchrophasor Data Against Spoofing Attacks in Smart Grids. United States. doi:10.1109/TSG.2019.2891852.
Cui, Yi, Bai, Feifei, Liu, Yilu, Fuhr, Peter L., and Morales-Rodriguez, Marissa E. Wed . "Spatio-Temporal Characterization of Synchrophasor Data Against Spoofing Attacks in Smart Grids". United States. doi:10.1109/TSG.2019.2891852.
@article{osti_1564165,
title = {Spatio-Temporal Characterization of Synchrophasor Data Against Spoofing Attacks in Smart Grids},
author = {Cui, Yi and Bai, Feifei and Liu, Yilu and Fuhr, Peter L. and Morales-Rodriguez, Marissa E.},
abstractNote = {“Source ID Mix” has emerged as a new type of highly deceiving attack which can alter the source information of synchrophasor data measured by multiple phasor measurement units, thereby paralyzing many wide-area measurement systems applications. To address such sophisticated cyber attacks, we have exploited the spatio-temporal characteristics of synchrophasor data for authenticating measurements’ source information. Specifically, the source authentication is performed when the measurements are subjected to three types of spoofing attacks. Some practical difficulties in applying the proposed method on real-time authentication caused by insufficient measurement data have also been solved. Experimental results with real synchrophasor measurements have validated the effectiveness of the proposed method in detecting such complicated data spoofing and improving power systems’ cyber security.},
doi = {10.1109/TSG.2019.2891852},
journal = {IEEE Transactions on Smart Grid},
number = 5,
volume = 10,
place = {United States},
year = {2019},
month = {1}
}

Journal Article:
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This content will become publicly available on January 9, 2020
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