Enhanced hidden moving target defense in smart grids
Recent research has proposed a moving target defense (MTD) approach that actively changes transmission line susceptance to preclude stealthy false data injection (FDI) attacks against the state estimation of a smart grid. However, existing studies were often conducted under a weak adversarial settin...
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sg-ntu-dr.10356-901092020-03-07T11:49:01Z Enhanced hidden moving target defense in smart grids Tian, Jue Tan, Rui Guan, Xiaohong Liu, Ting School of Computer Science and Engineering DRNTU::Engineering::Computer science and engineering False Data Injection Attack Moving Target Defense Recent research has proposed a moving target defense (MTD) approach that actively changes transmission line susceptance to preclude stealthy false data injection (FDI) attacks against the state estimation of a smart grid. However, existing studies were often conducted under a weak adversarial setting, in that they ignore the possibility that alert attackers can also try to detect the activation of MTD before they launch the FDI attacks. We call this new threat as parameter confirming-first (PCF) FDI. To improve the stealthiness of MTD, we propose a hidden MTD approach that cannot be detected by the attackers and prove its equivalence to an MTD that maintains the power flows of the whole grid. Moreover, we analyze the completeness of MTD and show that any hidden MTD is incomplete in that FDI attacks may bypass the hidden MTD opportunistically. This result suggests that the stealthiness and completeness are two conflicting goals in MTD design. Finally, we propose an approach to enhancing the hidden MTD against a class of highly structured FDI attacks. We also discuss the MTD's operational costs under the dc and ac models. We conduct simulations to show the effectiveness of the hidden MTD against PCF-FDI attacks under realistic settings. Accepted version 2019-05-28T08:32:14Z 2019-12-06T17:40:51Z 2019-05-28T08:32:14Z 2019-12-06T17:40:51Z 2019 Journal Article Tian, J., Tan, R., Guan, X., & Liu, T. (2019). Enhanced Hidden Moving Target Defense in Smart Grids. IEEE Transactions on Smart Grid, 10(2), 2208-2223. doi:10.1109/TSG.2018.2791512 1949-3053 https://hdl.handle.net/10356/90109 http://hdl.handle.net/10220/48421 10.1109/TSG.2018.2791512 en IEEE Transactions on Smart Grid © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works. The published version is available at: https://doi.org/10.1109/TSG.2018.2791512. 15 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering False Data Injection Attack Moving Target Defense Tian, Jue Tan, Rui Guan, Xiaohong Liu, Ting Enhanced hidden moving target defense in smart grids |
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Recent research has proposed a moving target defense (MTD) approach that actively changes transmission line susceptance to preclude stealthy false data injection (FDI) attacks against the state estimation of a smart grid. However, existing studies were often conducted under a weak adversarial setting, in that they ignore the possibility that alert attackers can also try to detect the activation of MTD before they launch the FDI attacks. We call this new threat as parameter confirming-first (PCF) FDI. To improve the stealthiness of MTD, we propose a hidden MTD approach that cannot be detected by the attackers and prove its equivalence to an MTD that maintains the power flows of the whole grid. Moreover, we analyze the completeness of MTD and show that any hidden MTD is incomplete in that FDI attacks may bypass the hidden MTD opportunistically. This result suggests that the stealthiness and completeness are two conflicting goals in MTD design. Finally, we propose an approach to enhancing the hidden MTD against a class of highly structured FDI attacks. We also discuss the MTD's operational costs under the dc and ac models. We conduct simulations to show the effectiveness of the hidden MTD against PCF-FDI attacks under realistic settings. |
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School of Computer Science and Engineering |
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School of Computer Science and Engineering Tian, Jue Tan, Rui Guan, Xiaohong Liu, Ting |
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Article |
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Tian, Jue Tan, Rui Guan, Xiaohong Liu, Ting |
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Tian, Jue |
title |
Enhanced hidden moving target defense in smart grids |
title_short |
Enhanced hidden moving target defense in smart grids |
title_full |
Enhanced hidden moving target defense in smart grids |
title_fullStr |
Enhanced hidden moving target defense in smart grids |
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Enhanced hidden moving target defense in smart grids |
title_sort |
enhanced hidden moving target defense in smart grids |
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2019 |
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https://hdl.handle.net/10356/90109 http://hdl.handle.net/10220/48421 |
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