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Control variable classification, modeling and anomaly detection in Modbus/TCP SCADA systems

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  • Erez, Noam
  • Wool, Avishai

Abstract

This paper describes a novel domain-aware anomaly detection system that detects irregular changes in Modbus/TCP SCADA control register values. The research discovered the presence of three classes of registers: (i) sensor registers; (ii) counter registers; and (iii) constant registers. An automatic classifier was developed to identify these classes. Additionally, parameterized behavior models were created for each class. During its learning phase, the anomaly detection system used the classifier to identify the different types of registers and instantiated the model for each register based on its type. During the enforcement phase, the system detected deviations from the model. The anomaly detection system was evaluated using 131h of traffic from a production SCADA system. The classifier had a true positive classification rate of 93%. During the enforcement phase, a 0.86% false alarm rate was obtained for the correctly-classified registers.

Suggested Citation

  • Erez, Noam & Wool, Avishai, 2015. "Control variable classification, modeling and anomaly detection in Modbus/TCP SCADA systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 10(C), pages 59-70.
    • Handle: RePEc:eee:ijocip:v:10:y:2015:i:c:p:59-70
    DOI: 10.1016/j.ijcip.2015.05.001
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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:

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    2. Jarmakiewicz, Jacek & Parobczak, Krzysztof & Maślanka, Krzysztof, 2017. "Cybersecurity protection for power grid control infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 18(C), pages 20-33.
    3. Cheng-Hui Chou & Chi-Che Wu & Kuan-Chu Lu & I-Hsien Liu & Tien-Hsiang Chang & Chu-Fen Li & Jung-Shian Li, 2018. "Modbus Packet Analysis and Attack Mode for SCADA System," Journal of ICT, Design, Engineering and Technological Science, Juhriyansyah Dalle, vol. 2(2), pages 30-35.
    4. Wang, Wu & Harrou, Fouzi & Bouyeddou, Benamar & Senouci, Sidi-Mohammed & Sun, Ying, 2022. "Cyber-attacks detection in industrial systems using artificial intelligence-driven methods," International Journal of Critical Infrastructure Protection, Elsevier, vol. 38(C).
    5. CHERIFI, Tarek & HAMAMI, Lamia, 2018. "A practical implementation of unconditional security for the IEC 60780-5-101 SCADA protocol," International Journal of Critical Infrastructure Protection, Elsevier, vol. 20(C), pages 68-84.
    6. Desta, Alemayehu Addisu & Badis, Hakim & George, Laurent, 2018. "Demand response scheduling in industrial asynchronous production lines constrained by available power and production rate," Applied Energy, Elsevier, vol. 230(C), pages 1414-1424.

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