Challenges of machine learning based monitoring for industrial control system networks

Matti Mantere, Ilkka Uusitalo, Mirko Sailio, Sami Noponen

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    19 Citations (Scopus)

    Abstract

    Detecting network intrusions and anomalies in industrial control systems is growing in urgency. Such systems used to be isolated but are now being connected to the outside world. Even in the case of isolated networks, privileged users may still present various threats to the system, either accidentally or intentionally. Also malfunctions in devices may cause anomalous traffic. Anomaly detection based network monitoring and intrusion detection systems could be capable of discerning normal and aberrant traffic in industrial control systems, detecting security incidents in an early phase. In this paper we discuss the challenges for such a monitoring system. One of the challenges is which features best differentiate between anomalous and normal behaviour. In the analysis, special focus is placed on this selection
    Original languageEnglish
    Title of host publicationProceedings
    Subtitle of host publication 26th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2012
    Place of PublicationFukuoka, Japan
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages968-972
    ISBN (Print)978-1-4673-0867-0, 978-0-7695-4652-0
    DOIs
    Publication statusPublished - 2012
    MoE publication typeNot Eligible
    Event26th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2012 - Fukuoka, Japan
    Duration: 26 Mar 201229 Mar 2012

    Conference

    Conference26th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2012
    Abbreviated titleWAINA 2012
    CountryJapan
    CityFukuoka
    Period26/03/1229/03/12

    Keywords

    • Industrial control
    • intrusion detection
    • machine learning
    • monitoring
    • production facilities
    • protocols

    Fingerprint Dive into the research topics of 'Challenges of machine learning based monitoring for industrial control system networks'. Together they form a unique fingerprint.

  • Cite this

    Mantere, M., Uusitalo, I., Sailio, M., & Noponen, S. (2012). Challenges of machine learning based monitoring for industrial control system networks. In Proceedings: 26th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2012 (pp. 968-972). IEEE Institute of Electrical and Electronic Engineers. https://doi.org/10.1109/WAINA.2012.135