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A threat modeling language for generating attack graphs of substation automation systems

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  • Rencelj Ling, Engla
  • Ekstedt, Mathias

Abstract

The substation automation system consists of many different complex assets and data flows. The system is also often externally connected to allow for remote management. The complexity and remote access to the substation automation system makes it vulnerable to cyber attacks. It also makes it difficult to assess the overall security of the system. One method of assessing the potential threats against a system is threat modeling. In this paper we create a language for producing threat models specifically for the substation automation systems. We focus on the method used to create the language where we review industry designs, build the language based on existing languages and consider attack scenarios from a literature study. Finally we present the language, model two different attack scenarios and generate attack graphs from the threat models.

Suggested Citation

  • Rencelj Ling, Engla & Ekstedt, Mathias, 2023. "A threat modeling language for generating attack graphs of substation automation systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 41(C).
    • Handle: RePEc:eee:ijocip:v:41:y:2023:i:c:s1874548223000148
    DOI: 10.1016/j.ijcip.2023.100601
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    References listed on IDEAS

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    1. Halevi, Gali & Moed, Henk & Bar-Ilan, Judit, 2017. "Suitability of Google Scholar as a source of scientific information and as a source of data for scientific evaluation—Review of the Literature," Journal of Informetrics, Elsevier, vol. 11(3), pages 823-834.
    2. Moreira, Naiara & Molina, Elías & Lázaro, Jesús & Jacob, Eduardo & Astarloa, Armando, 2016. "Cyber-security in substation automation systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1552-1562.
    3. Giovanna Dondossola & Judit Szanto & Marcelo Masera & Igor Nai Fovino, 2008. "Effects of intentional threats to power substation control systems," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 4(1/2), pages 129-143.
    4. Lahza, Hassan & Radke, Kenneth & Foo, Ernest, 2018. "Applying domain-specific knowledge to construct features for detecting distributed denial-of-service attacks on the GOOSE and MMS protocols," International Journal of Critical Infrastructure Protection, Elsevier, vol. 20(C), pages 48-67.
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