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Applying domain-specific knowledge to construct features for detecting distributed denial-of-service attacks on the GOOSE and MMS protocols

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  • Lahza, Hassan
  • Radke, Kenneth
  • Foo, Ernest

Abstract

Electric substation automation systems based on the IEC 61850 standard predominantly employ the GOOSE and MMS protocols. Because GOOSE and MMS messages are not encrypted, an attacker can observe packet header information in protocol messages and inject large numbers of spoofed messages that can flood a substation automation system. Sophisticated machine-learning-based intrusion detection systems are required to detect these types of distributed denial-of-service attacks. However, the performance of machine-learning-based classifiers is hindered by the relative lack of features that express GOOSE and MMS protocol behavior.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ijocip:v:20:y:2018:i:c:p:48-67
    DOI: 10.1016/j.ijcip.2017.12.002
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    References listed on IDEAS

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    1. Matti Mantere & Mirko Sailio & Sami Noponen, 2013. "Network Traffic Features for Anomaly Detection in Specific Industrial Control System Network," Future Internet, MDPI, vol. 5(4), pages 1-14, September.
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    Cited by:

    1. Yadav, Geeta & Paul, Kolin, 2021. "Architecture and security of SCADA systems: A review," International Journal of Critical Infrastructure Protection, Elsevier, vol. 34(C).
    2. 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).

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