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Accurate modeling of Modbus/TCP for intrusion detection in SCADA systems

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  • Goldenberg, Niv
  • Wool, Avishai

Abstract

The Modbus/TCP protocol is commonly used in SCADA systems for communications between a human–machine interface (HMI) and programmable logic controllers (PLCs). This paper presents a model-based intrusion detection system designed specifically for Modbus/TCP networks. The approach is based on the key observation that Modbus traffic to and from a specific PLC is highly periodic; as a result, each HMI-PLC channel can be modeled using its own unique deterministic finite automaton (DFA). An algorithm is presented that can automatically construct the DFA associated with an HMI-PLC channel based on about 100 captured messages. The resulting DFA-based intrusion detection system looks deep into Modbus/TCP packets and produces a very detailed traffic model. This approach is very sensitive and is able to flag anomalies such as a message appearing out of its position in the normal sequence or a message referring to a single unexpected bit. The intrusion detection approach is tested on a production Modbus system. Despite its high sensitivity, the system has a very low false positive rate—perfect matches of the model to the traffic were observed for five of the seven PLCs tested without a single false alarm over 111h of operation. Furthermore, the intrusion detection system successfully flagged real anomalies that were caused by technicians who were troubleshooting the HMI system. The system also helped identify a PLC that was configured incorrectly.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ijocip:v:6:y:2013:i:2:p:63-75
    DOI: 10.1016/j.ijcip.2013.05.001
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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. Bowen Xing & Yafeng Jiang & Yuqing Liu & Shouqi Cao, 2018. "Risk Data Analysis Based Anomaly Detection of Ship Information System," Energies, MDPI, vol. 11(12), pages 1-16, December.
    3. Vosughi, Amirkhosro & Tamimi, Ali & King, Alexandra Beatrice & Majumder, Subir & Srivastava, Anurag K., 2022. "Cyber–physical vulnerability and resiliency analysis for DER integration: A review, challenges and research needs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    4. 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.
    5. 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.
    6. Urrea, Claudio & Morales, Claudio & Kern, John, 2016. "Implementation of error detection and correction in the Modbus-RTU serial protocol," International Journal of Critical Infrastructure Protection, Elsevier, vol. 15(C), pages 27-37.
    7. Genge, Béla & Graur, Flavius & Haller, Piroska, 2015. "Experimental assessment of network design approaches for protecting industrial control systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 11(C), pages 24-38.
    8. adepu, Sridhar & Mathur, Aditya, 2021. "SafeCI: Avoiding process anomalies in critical infrastructure," International Journal of Critical Infrastructure Protection, Elsevier, vol. 34(C).
    9. 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).
    10. 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.
    11. 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.
    12. Vlad Daniel SAVIN & Costel SERBAN, 2019. "Cybersecurity Vulnerabilities And Threats Of Scada Systems In Critical Infrastructures," Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 13(1), pages 234-237, November.
    13. Knowles, William & Prince, Daniel & Hutchison, David & Disso, Jules Ferdinand Pagna & Jones, Kevin, 2015. "A survey of cyber security management in industrial control systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 9(C), pages 52-80.
    14. 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.
    15. Khalili, Abdullah & Sami, Ashkan & Khozaei, Amin & Pouresmaeeli, Saber, 2018. "SIDS: State-based intrusion detection for stage-based cyber physical systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 22(C), pages 113-124.
    16. Farsi, Hamed & Fanian, Ali & Taghiyarrenani, Zahra, 2019. "A novel online state-based anomaly detection system for process control networks," International Journal of Critical Infrastructure Protection, Elsevier, vol. 27(C).

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