Spatio-Temporal Characterization of Synchrophasor Data Against Spoofing Attacks in Smart Grids
Article
Article Title | Spatio-Temporal Characterization of Synchrophasor Data Against Spoofing Attacks in Smart Grids |
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ERA Journal ID | 123777 |
Article Category | Article |
Authors | Cui, Yi (Author), Bai, Feifei (Author), Liu, Yilu (Author), Fuhr, Peter L. (Author) and Morales-Rodriguez, Marissa E. (Author) |
Journal Title | IEEE Transactions on Smart Grid |
Journal Citation | 10 (5), pp. 5807-5818 |
Number of Pages | 12 |
Year | 2019 |
Place of Publication | United States |
ISSN | 1949-3053 |
1949-3061 | |
Digital Object Identifier (DOI) | https://doi.org/10.1109/tsg.2019.2891852 |
Web Address (URL) | https://ieeexplore.ieee.org/document/8606277 |
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(PMUs), thereby paralyzing many wide-area measurement systems(WAMS) 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. |
Keywords | Cyber security; Machine learning; Phasor measurement unit (PMU); Spoofing attack; Wide-area measurement systems (WAMS) |
ANZSRC Field of Research 2020 | 460403. Data security and protection |
400803. Electrical energy generation (incl. renewables, excl. photovoltaics) | |
460308. Pattern recognition | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | University of Tennessee, United States |
University of Queensland | |
Oak Ridge National Laboratory, United States | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q7w12/spatio-temporal-characterization-of-synchrophasor-data-against-spoofing-attacks-in-smart-grids
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