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Abstraction-Based Synthesis of Controllers for Approximate Opacity
Shanghai Jiao Tong University, Key Laboratory of System Control and Information Processing, Department of Automation, Shanghai, China.
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0002-3199-4015
Shanghai Jiao Tong University, Key Laboratory of System Control and Information Processing, Department of Automation, Shanghai, China.
University of Colorado, Department of Computer Science, Boulder, CO, USA; LMU Munich, Department of Computer Science, Munich, Germany.
2023 (English)In: 2023 62nd IEEE Conference on Decision and Control, CDC 2023, Institute of Electrical and Electronics Engineers (IEEE) , 2023, p. 7930-7936Conference paper, Published paper (Refereed)
Abstract [en]

Opacity is an important information-flow security property which characterizes the plausible deniability of certain 'secret behaviors' in dynamical systems. In this paper, we study the problem of synthesizing controllers enforcing a notion of opacity over discrete-time control systems with continuous state sets. In this paper, we develop an abstraction-based approach to tackle the controller synthesis problem. Specifically, we adopt a notion of approximate opacity which is suitable for continuous-space control systems. We propose a notion of approximate initial-state opacity preserving alternating simulation relation which characterizes the closeness between two systems in terms of opacity preservation. We show that, based on this new notion of system relation, one can synthesize an opacity-enforcing controller for the abstract system which is finite and then refine it back to enforce opacity over the original control system. Finally, we present a method for constructing opacity-preserving finite abstractions for discrete-time control systems under some stability properties. Our results are illustrated on a two-room temperature control problem.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2023. p. 7930-7936
Series
Proceedings of the IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-343708DOI: 10.1109/CDC49753.2023.10383482Scopus ID: 2-s2.0-85184830556OAI: oai:DiVA.org:kth-343708DiVA, id: diva2:1839903
Conference
62nd IEEE Conference on Decision and Control, CDC 2023, Singapore, Singapore, Dec 13 2023 - Dec 15 2023
Note

QC 20240223

Part of ISBN 979-8-3503-0124-3

Available from: 2024-02-22 Created: 2024-02-22 Last updated: 2024-02-29Bibliographically approved

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Liu, Siyuan

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