RAGIIoT: Risk-aware attack graph generation for IIoT via automated CVE-tactic mapping

Li, Shancang and Liu, Yifan 2025. RAGIIoT: Risk-aware attack graph generation for IIoT via automated CVE-tactic mapping. Presented at: IEEE/ACM International Symposium on Quality of Service, Gold Coast, Australia, 2–4 July 2025. Item availability restricted.

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Abstract

The complexity of Industrial IoT (IIoT) environments introduces cyber risks, especially where legacy and modern systems converge. This paper focuses on a lightweight dynamic threats analysis framework by converting static attack graphs into dynamic probabilistic attack graphs (PAGs). Utilising real-time anomalies, CVSS vulnerabilities, and MITRE ATT\&CK\textsuperscript{\textregistered} mappings, it quantifies threat propagation via probabilistic inference. Edges are dynamically weighted by tactic relevance, exploit severity, and device criticality, adapting to evolving attack chains. QoS-aware risk prioritization balances mitigation urgency, asset availability, and performance, optimizing resource allocation. This enables proactive defense in resource-constrained IIoT environments while ensuring operational continuity.

Item Type:	Conference or Workshop Item (Poster)
Status:	In Press
Schools:	Schools > Computer Science & Informatics
Date of First Compliant Deposit:	23 May 2025
Date of Acceptance:	21 May 2025
Last Modified:	26 Jun 2025 15:45
URI:	https://orca.cardiff.ac.uk/id/eprint/178462

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