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  • Open Access

    ARTICLE

    Event-Based Anomaly Detection for Non-Public Industrial Communication Protocols in SDN-Based Control Systems

    Ming Wan1, Jiangyuan Yao2,*, Yuan Jing1, Xi Jin3,4

    CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 447-463, 2018, DOI:10.3970/cmc.2018.02195

    Abstract As the main communication mediums in industrial control networks, industrial communication protocols are always vulnerable to extreme exploitations, and it is very difficult to take protective measures due to their serious privacy. Based on the SDN (Software Defined Network) technology, this paper proposes a novel event-based anomaly detection approach to identify misbehaviors using non-public industrial communication protocols, and this approach can be installed in SDN switches as a security software appliance in SDN-based control systems. Furthermore, aiming at the unknown protocol specification and message format, this approach first restructures the industrial communication sessions and merges More >

  • Open Access

    ARTICLE

    Anomaly Detection

    Nadipuram R. Prasad1, Salvador Almanza-Garcia1, Thomas T. Lu2

    CMC-Computers, Materials & Continua, Vol.14, No.1, pp. 1-22, 2009, DOI:10.3970/cmc.2009.014.001

    Abstract The paper presents a revolutionary framework for the modeling, detection, characterization, identification, and machine-learning of anomalous behavior in observed phenomena arising from a large class of unknown and uncertain dynamical systems. An evolved behavior would in general be very difficult to correct unless the specific anomalous event that caused such behavior can be detected early, and any consequence attributed to the specific anomaly following its detection. Substantial investigative time and effort is required to back-track the cause for abnormal behavior and to recreate the event sequence leading to such abnormal behavior. The need to automatically More >

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