A Measurement Source Authentication Methodology for Power System Cyber Security Enhancement
Article
Article Title | A Measurement Source Authentication Methodology for Power System Cyber Security Enhancement |
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ERA Journal ID | 123777 |
Article Category | Article |
Authors | Cui, Yi (Author), Bai, Feifei (Author), Liu, Yong (Author) and Liu, Yilu (Author) |
Journal Title | IEEE Transactions on Smart Grid |
Journal Citation | 9 (4), pp. 3914-3916 |
Number of Pages | 3 |
Year | 2018 |
Place of Publication | United States |
ISSN | 1949-3053 |
1949-3061 | |
Digital Object Identifier (DOI) | https://doi.org/10.1109/TSG.2018.2826444 |
Web Address (URL) | https://ieeexplore.ieee.org/document/8344506 |
Abstract | This letter proposes a spatial signature-based power system measurement source identification and authentication methodology. A mathematical morphology method is used to decompose the power system measurement signals and obtain the intrinsic components, which sparsity trends and roughness values are further derived to establish the time-frequency (TF) sparsity mapping. Then random forest classification is utilized to correlate the correct measurement source for each measurement signal based on the derived TF sparsity mapping. Experiment results using five phasor measurement units has validated the effectiveness of this methodology. |
Keywords | Cyber security; measurement; phasor measurement unit (PMU); source authentication; spatial signature |
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 | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q7w20/a-measurement-source-authentication-methodology-for-power-system-cyber-security-enhancement
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