Bhole, M., Kastner, W., & Sauter, T. (2022). A Model Based Framework for Testing Safety and Security in Operational Technology Environments. In 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA) (pp. 1–4). https://doi.org/10.1109/ETFA52439.2022.9921549
E191-03 - Forschungsbereich Automation Systems E384-01 - Forschungsbereich Software-intensive Systems
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Published in:
2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)
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ISBN:
978-1-6654-9996-5
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Volume:
2022-September
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Date (published):
24-Oct-2022
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Event name:
2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)
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Event date:
6-Sep-2022 - 9-Sep-2022
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Event place:
Stuttgart, Germany
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Number of Pages:
4
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Peer reviewed:
Yes
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Keywords:
Industrial Control System; Model-Based Testing; Operational Technology; Safety and Security
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Abstract:
Today's industrial control systems consist of tightly coupled components allowing adversaries to exploit security attack surfaces from the information technology side, and, thus, also get access to automation devices residing at the operational technology level to compromise their safety functions. To identify these concerns, we propose a model-based testing approach which we consider a promising way to analyze the safety and security behavior of a system under test providing means to protect its components and to increase the quality and efficiency of the overall system. The structure of the underlying framework is divided into four parts, according to the critical factors in testing of operational technology environments. As a first step, this paper describes the ingredients of the envisioned framework. A system model allows to overview possible attack surfaces, while the foundations of testing and the recommendation of mitigation strategies will be based on process-specific safety and security standard procedures with the combination of existing vulnerability databases.
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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%