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Hybrid ontology for safety, security, and dependability risk assessments and Security Threat Analysis (STA) method for industrial control systems

  • Jarmo Alanen*
  • , Joonas Linnosmaa
  • , Timo Malm
  • , Nikolaos Papakonstantinou
  • , Toni Ahonen
  • , Eetu Heikkilä
  • , Risto Tiusanen*
  • *Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

This paper introduces a model-based methodology for hybrid reliability, availability, maintainability, safety, and security (RAMSS) risk assessment management, which extends our previous work of model-based, data-driven, support for engineering mission-critical systems. It represents a hybrid risk assessment ontology, which harmonises basic concepts between dependability, safety and security based on well-known industrial standards. Based on the proposed ontology, we create a cybersecurity risk analysis method, called Security Threat Analysis (STA), for industrial control systems and successfully demonstrate the method. For the demonstration, we introduce a data model for creating a tool-supported data repository for STA, then implement this repository with a commercial-off-the-shelf tool. We use the repository to carry out an exemplary STA of a nuclear fuel pool cooling control system, assessing a cybersecurity-related hazard. The demonstration suggests that the hybrid RAMSS risk assessment ontology and the related STA data model are ready to be tested in industrial use, offering a structured data repository to support assessment and traceability between the created artefacts.
Original languageEnglish
Article number108270
Number of pages20
JournalReliability Engineering and System Safety
Volume220
DOIs
Publication statusPublished - Apr 2022
MoE publication typeA1 Journal article-refereed

Funding

The Finnish Research Programme on Nuclear Power Plant Safety 2019-2022 (SAFIR2022) funded this research. Furthermore, the study on the dependability aspects of the risk assessment ontology was done within a national co-innovation project, AUTOPORT, financed by Business Finland, VTT and other participating companies.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • Cybersecurity analysis method
  • Hybrid risk assessment
  • Industrial control systems
  • Model-based system engineering
  • Ontology

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