Esnaola, I. orcid.org/0000-0001-5597-1718, Perlaza, S.M., Poor, H.V. et al. (1 more author) (2016) Maximum Distortion Attacks in Electricity Grids. IEEE Transactions on Smart Grid, 7 (4). pp. 2007-2015. ISSN 1949-3053
Abstract
Multiple attacker data-injection attack construction in electricity grids with minimum-mean-square-error state estimation is studied for centralized and decentralized scenarios. A performance analysis of the trade-off between the maximum distortion that an attack can introduce and the probability of the attack being detected by the network operator is considered. In this setting, optimal centralized attack construction strategies are studied. The decentralized case is examined in a game-theoretic setting. A novel utility function is proposed to model this trade-off and it is shown that the resulting game is a potential game. The existence and cardinality of the corresponding set of Nash equilibria of the game is analyzed. Interestingly, the attackers can exploit the correlation among the state variables to facilitate the attack construction. It is shown that attackers can agree on a data-injection vector construction that achieves the best trade-off between distortion and detection probability by sharing only a limited number of bits offline. For the particular case of two attackers, numerical results based on IEEE test systems are presented.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 22 May 2018 14:48 |
Last Modified: | 22 May 2018 14:48 |
Published Version: | https://doi.org/10.1109/TSG.2016.2550420 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/TSG.2016.2550420 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:130245 |