A Runtime Verification Framework for Cyber-Physical Systems Based on Data Analytics and LTL Formula Learning
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Hou, Z
Foo, E
Li, Q
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Brisbane, Australia
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Abstract
Safeguarding individuals and valuable resources from cyber threats stands as a paramount concern in the digital landscape, encompassing realms like cyber-physical systems and IoT systems. The safeguarding of cyber-physical systems (CPS) is particularly challenging given their intricate infrastructure, necessitating ongoing real-time analysis and swift responses to potential threats. Our proposition introduces a digital twin framework built upon runtime verification, effectively harnessing the capabilities of data analytics and the acquisition of Linear Temporal Logic (LTL) formulas. We demonstrate the efficacy of our approach through an application to water distribution systems.
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Formal Methods and Software Engineering 24th International Conference on Formal Engineering Methods, ICFEM 2023, Brisbane, QLD, Australia, November 21–24, 2023, Proceedings
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14308
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© 2023. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. The original publication is available at http://doi.org/10.1007/978-981-99-7584-6_19
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Data management and data science
Information and computing sciences
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Akande, AJ; Hou, Z; Foo, E; Li, Q, A Runtime Verification Framework for Cyber-Physical Systems Based on Data Analytics and LTL Formula Learning, Formal Methods and Software Engineering 24th International Conference on Formal Engineering Methods, ICFEM 2023, Brisbane, QLD, Australia, November 21–24, 2023, Proceedings, 2023, 14308, pp. 273-278