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Security Measure Allocation for Industrial Control Systems: Exploiting Systematic Search Techniques and Submodularity
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.ORCID iD: 0000-0001-5491-4068
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2018 (English)In: International Journal of Robust and Nonlinear Control, ISSN 1049-8923, E-ISSN 1099-1239Article in journal (Refereed) Published
Abstract [en]

To protect industrial control systems from cyberattacks, multiple layers of security measures need to be allocated to prevent critical security vulnerabilities. However, both finding the critical vulnerabilities and then allocating security measures in a cost‐efficient way become challenging when the number of vulnerabilities and measures is large. This paper proposes a framework that can be used once this is the case. In our framework, the attacker exploits security vulnerabilities to gain control over some of the sensors and actuators. The critical vulnerabilities are those that are not complex to exploit and can lead to a large impact on the physical world through the compromised sensors and actuators. To find these vulnerabilities efficiently, we propose an algorithm that uses the nondecreasing properties of the impact and complexity functions and properties of the security measure allocation problem to speed up the search. Once the critical vulnerabilities are located, the security measure allocation problem reduces to an integer linear program. Since integer linear programs are NP‐hard in general, we reformulate this problem as a problem of minimizing a linear set function subject to a submodular constraint. A polynomial time greedy algorithm can then be applied to obtain a solution with guaranteed approximation bound. The applicability of our framework is demonstrated on a control system used for regulation of temperature within a building.

Place, publisher, year, edition, pages
2018.
National Category
Control Engineering
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URN: urn:nbn:se:uu:diva-363605DOI: 10.1002/rnc.4375OAI: oai:DiVA.org:uu-363605DiVA, id: diva2:1256980
Available from: 2018-10-18 Created: 2018-10-18 Last updated: 2019-06-20Bibliographically approved

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Teixeira, André

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