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Title: Enhanced hidden moving target defense in smart grids
Authors: Tian, Jue
Tan, Rui
Guan, Xiaohong
Liu, Ting
Keywords: DRNTU::Engineering::Computer science and engineering
False Data Injection Attack
Moving Target Defense
Issue Date: 2019
Source: 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
Series/Report no.: IEEE Transactions on Smart Grid
Abstract: 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.
ISSN: 1949-3053
DOI: 10.1109/TSG.2018.2791512
Rights: © 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:
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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