Analysis of moving target defense against false data injection attacks on power grid

Recent studies have considered thwarting false data injection (FDI) attacks against state estimation in power grids by proactively perturbing branch susceptances. This approach is known as moving target defense (MTD). However, despite of the deployment of MTD, it is still possible for the attacker t...

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Main Authors: Zhang, Z., Deng, Ruilong, Yau, D. K. Y., Cheng, P., Chen, J.
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/154436
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1544362021-12-22T08:04:39Z Analysis of moving target defense against false data injection attacks on power grid Zhang, Z. Deng, Ruilong Yau, D. K. Y. Cheng, P. Chen, J. School of Computer Science and Engineering Engineering::Computer science and engineering Power Grids Cyber-Physical System (CPS) Recent studies have considered thwarting false data injection (FDI) attacks against state estimation in power grids by proactively perturbing branch susceptances. This approach is known as moving target defense (MTD). However, despite of the deployment of MTD, it is still possible for the attacker to launch stealthy FDI attacks generated with former branch susceptances. In this paper, we prove that, an MTD has the capability to thwart all FDI attacks constructed with former branch susceptances only if (i) the number of branches l in the power system is not less than twice that of the system states n (i.e., l \geq 2n , where n + 1 is the number of buses); (ii) the susceptances of more than n branches, which cover all buses, are perturbed. Moreover, we prove that the state variable of a bus that is only connected by a single branch (no matter it is perturbed or not) can always be modified by the attacker. Nevertheless, in order to reduce the attack opportunities of potential attackers, we first exploit the impact of the susceptance perturbation magnitude on the dimension of the stealthy attack space, in which the attack vector is constructed with former branch susceptances. Then, we propose that, by perturbing an appropriate set of branches, we can minimize the dimension of the stealthy attack space and maximize the number of covered buses. Besides, we consider the increasing operation cost caused by the activation of MTD. Finally, we conduct extensive simulations to illustrate our findings with IEEE standard test power systems. Agency for Science, Technology and Research (A*STAR) Nanyang Technological University This work was supported in part by the National Key Research and Development Program of China under Grant 2016YFB0800204, in part by the National Natural Science Foundation of China under Grant 61833015, in part by the Singapore University of Technology and Design-Zhejiang University Innovation, Design and Entrepreneurship Alliance (SUTD-ZJU IDEA) under Award 201805, in part by the Nanyang Technological University (NTU) Internal Funding-Start-up Grant (SUG)- the College of Engineering (CoE) under Grant M4082287, and in part by the A*STAR- Nanyang Technological University-Singapore University of Technology and Design AI Partnership under Grant RGANS1906. This article was presented at the IEEE PES ISGT 2019 [1]. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Walid Saad. 2021-12-22T08:04:39Z 2021-12-22T08:04:39Z 2020 Journal Article Zhang, Z., Deng, R., Yau, D. K. Y., Cheng, P. & Chen, J. (2020). Analysis of moving target defense against false data injection attacks on power grid. IEEE Transactions On Information Forensics and Security, 15, 2320-2335. https://dx.doi.org/10.1109/TIFS.2019.2928624 1556-6013 https://hdl.handle.net/10356/154436 10.1109/TIFS.2019.2928624 2-s2.0-85069906819 15 2320 2335 en 201805 M4082287 RGANS1906 IEEE Transactions on Information Forensics and Security © 2019 IEEE. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Power Grids
Cyber-Physical System (CPS)
spellingShingle Engineering::Computer science and engineering
Power Grids
Cyber-Physical System (CPS)
Zhang, Z.
Deng, Ruilong
Yau, D. K. Y.
Cheng, P.
Chen, J.
Analysis of moving target defense against false data injection attacks on power grid
description Recent studies have considered thwarting false data injection (FDI) attacks against state estimation in power grids by proactively perturbing branch susceptances. This approach is known as moving target defense (MTD). However, despite of the deployment of MTD, it is still possible for the attacker to launch stealthy FDI attacks generated with former branch susceptances. In this paper, we prove that, an MTD has the capability to thwart all FDI attacks constructed with former branch susceptances only if (i) the number of branches l in the power system is not less than twice that of the system states n (i.e., l \geq 2n , where n + 1 is the number of buses); (ii) the susceptances of more than n branches, which cover all buses, are perturbed. Moreover, we prove that the state variable of a bus that is only connected by a single branch (no matter it is perturbed or not) can always be modified by the attacker. Nevertheless, in order to reduce the attack opportunities of potential attackers, we first exploit the impact of the susceptance perturbation magnitude on the dimension of the stealthy attack space, in which the attack vector is constructed with former branch susceptances. Then, we propose that, by perturbing an appropriate set of branches, we can minimize the dimension of the stealthy attack space and maximize the number of covered buses. Besides, we consider the increasing operation cost caused by the activation of MTD. Finally, we conduct extensive simulations to illustrate our findings with IEEE standard test power systems.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Zhang, Z.
Deng, Ruilong
Yau, D. K. Y.
Cheng, P.
Chen, J.
format Article
author Zhang, Z.
Deng, Ruilong
Yau, D. K. Y.
Cheng, P.
Chen, J.
author_sort Zhang, Z.
title Analysis of moving target defense against false data injection attacks on power grid
title_short Analysis of moving target defense against false data injection attacks on power grid
title_full Analysis of moving target defense against false data injection attacks on power grid
title_fullStr Analysis of moving target defense against false data injection attacks on power grid
title_full_unstemmed Analysis of moving target defense against false data injection attacks on power grid
title_sort analysis of moving target defense against false data injection attacks on power grid
publishDate 2021
url https://hdl.handle.net/10356/154436
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