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Exploiting traffic periodicity in industrial control networks

Author

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  • Barbosa, Rafael Ramos Regis
  • Sadre, Ramin
  • Pras, Aiko

Abstract

Industrial control systems play a major role in the operation of critical infrastructure assets. Due to the polling mechanisms typically used to retrieve data from field devices, industrial control network traffic exhibits strong periodic patterns. This paper presents a novel approach that uses message repetition and timing information to automatically learn traffic models that capture the periodic patterns. The feasibility of the approach is demonstrated using three traffic traces collected from real-world industrial networks. Two practical applications for the learned models are presented. The first is their use in intrusion detection systems; the learned models represent whitelists of valid commands and the frequencies at which they are sent; thus, the models may be used to detect data injection and denial-of-service attacks. The second application is to generate synthetic traffic traces, which can be used to test intrusion detection systems and evaluate the performance of industrial control devices.

Suggested Citation

  • Barbosa, Rafael Ramos Regis & Sadre, Ramin & Pras, Aiko, 2016. "Exploiting traffic periodicity in industrial control networks," International Journal of Critical Infrastructure Protection, Elsevier, vol. 13(C), pages 52-62.
  • Handle: RePEc:eee:ijocip:v:13:y:2016:i:c:p:52-62
    DOI: 10.1016/j.ijcip.2016.02.004
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    References listed on IDEAS

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    1. Goldenberg, Niv & Wool, Avishai, 2013. "Accurate modeling of Modbus/TCP for intrusion detection in SCADA systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 6(2), pages 63-75.
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    Cited by:

    1. SICARD, Franck & ZAMAI, Éric & FLAUS, Jean-Marie, 2019. "An approach based on behavioral models and critical states distance notion for improving cybersecurity of industrial control systems," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 584-603.
    2. Haller, Piroska & Genge, Béla & Duka, Adrian-Vasile, 2019. "On the practical integration of anomaly detection techniques in industrial control applications," International Journal of Critical Infrastructure Protection, Elsevier, vol. 24(C), pages 48-68.
    3. Lin, Chih-Yuan & Nadjm-Tehrani, Simin, 2023. "Protocol study and anomaly detection for server-driven traffic in SCADA networks," International Journal of Critical Infrastructure Protection, Elsevier, vol. 42(C).

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