Publication Type

Journal Article

Version

publishedVersion

Publication Date

9-2026

Abstract

Cyber-physical systems increasingly rely on interconnected physical and digital systems whose security incidents can escalate rapidly into safety and operational failures. Existing decision-support approaches struggle to support incident response because they rely on static assumptions, incomplete vulnerability data, and single-objective risk models that do not adequately capture trade-offs between attack success likelihood, impact severity, and system availability. This paper proposes an adaptive decision-support framework for incident mitigation in cyber-physical systems that integrates hierarchical Bayesian Network modelling, confidence-calibrated exposure estimation, and multi-objective optimisation into a unified, adaptive pipeline. The framework constructs probabilistic models from system architecture and vulnerability data, incorporating complementary vulnerability scores under epistemic uncertainty as conservative, uncertainty-aware reporting metrics for supporting downstream risk assessment. Mitigation strategies are explored as countermeasure portfolios and refined using multi-objective optimisation to identify Pareto-optimal trade-offs suitable for incident response scenarios. Frequency-based heuristics are applied to prioritise mitigation actions across optimisation runs. The framework is evaluated on three representative cyber-physical attack scenarios, demonstrating its ability to adapt to evolving threats and provide actionable decision support under operational constraints, with the aim of enhancing the resilience of cyber-physical systems.

Keywords

Bayesian Networks, cyber-physical systems, decision-support systems, incident response, multi-objective optimisation

Discipline

Information Security | Software Engineering

Research Areas

Software Systems; Cybersecurity

Areas of Excellence

Digital transformation

Publication

IEEE Access

Volume

14

First Page

148923

Last Page

148942

ISSN

2169-3536

Identifier

10.1109/ACCESS.2026.3735972

Publisher

Institute of Electrical and Electronics Engineers

Embargo Period

10-2-2026

Additional URL

https://doi.org/10.1109/ACCESS.2026.3735972

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