Bhosale, P., Kastner, W., & Sauter, T. (2023). Integrated Safety-Security Risk Assessment for Industrial Control System: An Ontology-based Approach. In 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA) (pp. 1–8). IEEE. https://doi.org/10.1109/ETFA54631.2023.10275530
E191-03 - Forschungsbereich Automation Systems E384-01 - Forschungsbereich Software-intensive Systems
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Published in:
2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA)
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ISBN:
9798350339918
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Date (published):
12-Oct-2023
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Event name:
2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA)
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Event date:
12-Sep-2023 - 15-Sep-2023
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Event place:
Sinaia, Romania
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Number of Pages:
8
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Publisher:
IEEE, Piscataway
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Peer reviewed:
Yes
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Keywords:
industrial control system; ontology; risk assessment; safety; security
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Abstract:
Industrial control systems (ICSs) are critical to the operation of industrial processes and critical infrastructure. Safety and security are crucial in any system or process, particularly in ICSs where failures can lead to severe consequences such as injury, loss of life, and damage to equipment and infrastructure. However, safety and security are often considered separately during the concept and design stages. An integrated risk assessment approach can combine safety and security considerations and provide a holistic evaluation of the overall risk to ICSs. Ontology-based approaches provide a systematic and structured method for representing knowledge and concepts related to risk assessment in industry. The aim of this paper is to develop an ontology based approach and generate a concept for integrating safety and security risk assessment. A case study is analysed using the ontology with a SPARQL query example.
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Project title:
Automated Risk Management for Industrial Control Systems (TÜV Austria Holding AG)
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Research Areas:
Digital Transformation in Manufacturing: 20% Computer Engineering and Software-Intensive Systems: 60% Automation and Robotics: 20%