mlsanityData to 7 Oct 2026

Supporting Cybersecurity Risk Management for Medical Devices via the SECUMAN Ontology and Shapes

arXiv 2608.00698 ↗First posted 1 Aug 2026cs.CR cs.AIcited by 0

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Abstract (arXiv)

We propose the SECUMAN ontology and shapes for representing and analysing cybersecurity risk-management documentation for medical devices. Cybersecurity risks are increasingly relevant for connected medical devices and may have direct consequences for patient safety. Current risk-management files are often maintained as semi-structured natural language text, which makes consistency checking, certification review, and reuse difficult. SECUMAN provides a formal OWL-based vocabulary for modelling security-risk context, assessment, control measures, and residual-risk evaluation, and uses SHACL constraints to check structural completeness and conformity with the intended documentation model. The ontology is aligned with VDE Spec 90025 and the related RISKMAN ontology and shapes, while extending their safety-oriented approach to concepts relevant to cybersecurity risk documentation such as threat scenarios, protection goals, attacker profiles, exposure levels, assets, and secure design arguments. SECUMAN is intended to support automated first-pass validation, traceability, and integration of cybersecurity and safety risk-management documentation.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 63 references that are in the map. First posted on arXiv 1 Aug 2026.

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6 of 63 references.

References · 6

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  2. 2024A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Modelscited by 450
  3. 2020Integration of Formal Proof into Unified Assurance Cases with Isabelle/SACMcited by 5
  4. 2025CVE-LLM : Ontology-Assisted Automatic Vulnerability Evaluation Using Large Language Modelscited by 4
  5. 2025Structuring Security: A Survey of Cybersecurity Ontologies, Semantic Log Processing, and LLMs Applicationcited by 3
  6. 2017The Security Assessment Domain: A Survey of Taxonomies and Ontologiescited by 1

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