Du, M., Zhang, X. orcid.org/0000-0002-6063-959X, Flynn, D. et al. (1 more author) (2026) Proactive defence of cyber-physical networks against coordinated attacks with optimal resource allocation. IEEE Transactions on Industrial Cyber-Physical Systems. pp. 1-10. ISSN: 2832-7004
Abstract
Cyber-physical power systems (CPPSs) are more vulnerable to coordinated attacks on cyber-physical networks. In this context, this paper first assesses the impact of coordinated attacks and reveals the interdependence of cyber-physical networks in amplifying system vulnerability. To address this issue, a tri-level cyber-physical network defence (CPND) model is proposed to enable proactive defence of cyber-physical networks through optimal protection resource allocation against coordinated attacks. This model considers the cyber and physical network properties as well as their interdependence in CPPSs. Meanwhile, it incorporates the optimal allocation of control centres, providing more practical defence strategies against coordinated attacks. Then, a Column-and-Constraint Generation (C&CG) with optimality cuts algorithm is developed to solve the proposed CPND model, thereby improving computational efficiency. Numerical simulation results verify the superiority of the proposed approach.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2026 The Authors. Except as otherwise noted, this author-accepted version of a journal article published in IEEE Transactions on Industrial Cyber-Physical Systems is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | Joining processes; Modeling; Costing; Costs; Protection; Power systems; Resource management; Algorithms; Optimization; Limiting |
| Dates: |
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| Institution: | The University of Sheffield |
| Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > School of Electrical and Electronic Engineering |
| Funding Information: | Funder Grant number UK Research and Innovation MR/W011360/1 UK RESEARCH AND INNOVATION MR/W011360/1 MR/W011360/2 |
| Date Deposited: | 22 Jun 2026 13:59 |
| Last Modified: | 22 Jun 2026 13:59 |
| Status: | Published online |
| Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
| Refereed: | Yes |
| Identification Number: | 10.1109/ticps.2026.3705709 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:242326 |
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Filename: Final-TICPS-2026-6-17.pdf
Licence: CC-BY 4.0

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