Synthesis of the supremal covert attacker against unknown supervisors by using observations

In this paper, we consider the problem of synthesizing the supremal covert damage-reachable attacker, in the setup where the model of the supervisor is unknown to the adversary but the adversary has recorded a (prefix-closed) finite set of observations of the runs of the closed-loop system. The synt...

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Main Authors: Tai, Ruochen, Lin, Liyong, Zhu, Yuting, Su, Rong
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/166617
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1666172023-05-05T15:46:59Z Synthesis of the supremal covert attacker against unknown supervisors by using observations Tai, Ruochen Lin, Liyong Zhu, Yuting Su, Rong School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Cyber-Physical System Discrete-Event System In this paper, we consider the problem of synthesizing the supremal covert damage-reachable attacker, in the setup where the model of the supervisor is unknown to the adversary but the adversary has recorded a (prefix-closed) finite set of observations of the runs of the closed-loop system. The synthesized attacker needs to ensure both the damage-reachability and the covertness against all the supervisors which are consistent with the given set of observations. There is a gap between the de facto supremality, assuming the model of the supervisor is known, and the supremality that can be attained with a limited knowledge of the model of the supervisor, from the adversary's point of view. We consider the setup where the attacker can exercise sensor replacement/deletion attacks and actuator enablement/disablement attacks. The solution methodology proposed in this work is to reduce the synthesis of the supremal covert damage-reachable attacker, given the model of the plant and the finite set of observations, to the synthesis of the supremal safe supervisor for certain transformed plant, which shows the decidability of the observation-assisted covert attacker synthesis problem. The effectiveness of our approach is illustrated on a water tank example adapted from the literature. Agency for Science, Technology and Research (A*STAR) Submitted/Accepted version This research is supported by A*STAR, Singapore under its RIE2020 Advanced Manufacturing and Engineering (AME) Industry Alignment Fund – Pre Positioning (IAF-PP) (Award A19D6a0053). 2023-05-04T05:57:24Z 2023-05-04T05:57:24Z 2022 Journal Article Tai, R., Lin, L., Zhu, Y. & Su, R. (2022). Synthesis of the supremal covert attacker against unknown supervisors by using observations. IEEE Transactions On Automatic Control. https://dx.doi.org/10.1109/TAC.2022.3191393 0018-9286 https://hdl.handle.net/10356/166617 10.1109/TAC.2022.3191393 en A19D6a0053 IEEE Transactions on Automatic Control © 2022 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/TAC.2022.3191393. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Cyber-Physical System
Discrete-Event System
spellingShingle Engineering::Electrical and electronic engineering
Cyber-Physical System
Discrete-Event System
Tai, Ruochen
Lin, Liyong
Zhu, Yuting
Su, Rong
Synthesis of the supremal covert attacker against unknown supervisors by using observations
description In this paper, we consider the problem of synthesizing the supremal covert damage-reachable attacker, in the setup where the model of the supervisor is unknown to the adversary but the adversary has recorded a (prefix-closed) finite set of observations of the runs of the closed-loop system. The synthesized attacker needs to ensure both the damage-reachability and the covertness against all the supervisors which are consistent with the given set of observations. There is a gap between the de facto supremality, assuming the model of the supervisor is known, and the supremality that can be attained with a limited knowledge of the model of the supervisor, from the adversary's point of view. We consider the setup where the attacker can exercise sensor replacement/deletion attacks and actuator enablement/disablement attacks. The solution methodology proposed in this work is to reduce the synthesis of the supremal covert damage-reachable attacker, given the model of the plant and the finite set of observations, to the synthesis of the supremal safe supervisor for certain transformed plant, which shows the decidability of the observation-assisted covert attacker synthesis problem. The effectiveness of our approach is illustrated on a water tank example adapted from the literature.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Tai, Ruochen
Lin, Liyong
Zhu, Yuting
Su, Rong
format Article
author Tai, Ruochen
Lin, Liyong
Zhu, Yuting
Su, Rong
author_sort Tai, Ruochen
title Synthesis of the supremal covert attacker against unknown supervisors by using observations
title_short Synthesis of the supremal covert attacker against unknown supervisors by using observations
title_full Synthesis of the supremal covert attacker against unknown supervisors by using observations
title_fullStr Synthesis of the supremal covert attacker against unknown supervisors by using observations
title_full_unstemmed Synthesis of the supremal covert attacker against unknown supervisors by using observations
title_sort synthesis of the supremal covert attacker against unknown supervisors by using observations
publishDate 2023
url https://hdl.handle.net/10356/166617
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