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A real-time anomaly-based IDS for cyber-attack detection at the industrial process level of Critical Infrastructures

Author

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  • Clotet, Xavier
  • Moyano, José
  • León, Gladys

Abstract

This work presents a real time anomaly-based detection system designed to work at the industrial process level of Critical Infrastructures (CI). The system’s core algorithm is based on negative selection and works in two phases: it first learns from the normal behaviour of the process, and then performs detection and raises alarms each time an abnormal behaviour is found. The main goal of the proposed tool is the detection of attacks targeting the physical components or devices composing the industrial process level of CI such as electric, gas or water utilities. The proposed IDS uses a multi-agent approach to tackle the complex problem of monitoring large amounts of data coming from measurements recorded by Industrial Control Systems. It was built on an open source distributed computation system for real time analysis. This tool was developed, tested, and validated during the EU-funded project PREEMPTIVE. Detection results obtained on a water treatment plant laboratory are presented and discussed.

Suggested Citation

  • Clotet, Xavier & Moyano, José & León, Gladys, 2018. "A real-time anomaly-based IDS for cyber-attack detection at the industrial process level of Critical Infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 23(C), pages 11-20.
    • Handle: RePEc:eee:ijocip:v:23:y:2018:i:c:p:11-20
    DOI: 10.1016/j.ijcip.2018.08.002
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    References listed on IDEAS

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    1. Estefanía Etchevés Miciolino & Dario Di Noto & Federico Griscioli & Maurizio Pizzonia & Jörg Kippe & Steffen Pfrang & Xavier Clotet & Gladys León & Fatai Babatunde Kassim & David Lund & Elisa Cost, 2017. "Preemptive: an integrated approach to intrusion detection and prevention in industrial control systems," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 13(2/3), pages 206-237.
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    Cited by:

    1. Safari, Mohammad & Parvinnia, Elham & Haddad, Alireza Keshavarz, 2021. "Industrial intrusion detection based on the behavior of rotating machine," International Journal of Critical Infrastructure Protection, Elsevier, vol. 34(C).
    2. 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.
    3. Robles-Durazno, Andres & Moradpoor, Naghmeh & McWhinnie, James & Russell, Gordon & Maneru-Marin, Inaki, 2019. "PLC memory attack detection and response in a clean water supply system," International Journal of Critical Infrastructure Protection, Elsevier, vol. 26(C).
    4. Sándor, Hunor & Genge, Béla & Szántó, Zoltán & Márton, Lőrinc & Haller, Piroska, 2019. "Cyber attack detection and mitigation: Software Defined Survivable Industrial Control Systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 25(C), pages 152-168.

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