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Risk Data Analysis Based Anomaly Detection of Ship Information System

Author

Listed:
  • Bowen Xing

    (College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China
    These authors contributed equally to this work.)

  • Yafeng Jiang

    (College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China)

  • Yuqing Liu

    (College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China)

  • Shouqi Cao

    (College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China
    These authors contributed equally to this work.)

Abstract

Due to the vulnerability and high risk of the ship environment, the Ship Information System (SIS) should provide 24 hours of uninterrupted protection against network attacks. Therefore, the corresponding intrusion detection mechanism is proposed for this situation. Based on the collaborative control structure of SIS, this paper proposes an anomaly detection pattern based on risk data analysis. An intrusion detection method based on the critical state is proposed, and the corresponding analysis algorithm is given. In the Industrial State Modeling Language (ISML), risk data are determined by all relevant data, even in different subsystems. In order to verify the attack recognition effect of the intrusion detection mechanism, this paper takes the course/roll collaborative control task as an example to carry out simulation verification of the effectiveness of the intrusion detection mechanism.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:12:p:3403-:d:187852
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    References listed on IDEAS

    as
    1. DongHo Kang & ByoungKoo Kim & JungChan Na & KyoungSon Jhang, 2014. "Whitelists Based Multiple Filtering Techniques in SCADA Sensor Networks," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-7, May.
    2. 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.
    3. Stone, Samuel & Temple, Michael, 2012. "Radio-frequency-based anomaly detection for programmable logic controllers in the critical infrastructure," International Journal of Critical Infrastructure Protection, Elsevier, vol. 5(2), pages 66-73.
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