IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v14y2018i8p1550147718794615.html
   My bibliography  Save this article

A survey of intrusion detection on industrial control systems

Author

Listed:
  • Yan Hu
  • An Yang
  • Hong Li
  • Yuyan Sun
  • Limin Sun

Abstract

The modern industrial control systems now exhibit an increasing connectivity to the corporate Internet technology networks so as to make full use of the rich resource on the Internet. The increasing interaction between industrial control systems and the outside Internet world, however, has made them an attractive target for a variety of cyber attacks, raising a great need to secure industrial control systems. Intrusion detection technology is one of the most important security precautions for industrial control systems. It can effectively detect potential attacks against industrial control systems. In this survey, we elaborate on the characteristics and the new security requirements of industrial control systems. After that, we present a new taxonomy of intrusion detection systems for industrial control systems based on different techniques: protocol analysis based, traffic mining based, and control process analysis based. In addition, we analyze the advantages and disadvantages of different categories of intrusion detection systems and discuss some future developments of intrusion detection systems for industrial control systems, in order to promote further research on intrusion detection technology for industrial control systems.

Suggested Citation

  • Yan Hu & An Yang & Hong Li & Yuyan Sun & Limin Sun, 2018. "A survey of intrusion detection on industrial control systems," International Journal of Distributed Sensor Networks, , vol. 14(8), pages 15501477187, August.
    • Handle: RePEc:sae:intdis:v:14:y:2018:i:8:p:1550147718794615
    DOI: 10.1177/1550147718794615
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1550147718794615
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1550147718794615?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mohamed Amine Ferrag & Leandros Maglaras & Ahmed Ahmim & Makhlouf Derdour & Helge Janicke, 2020. "RDTIDS: Rules and Decision Tree-Based Intrusion Detection System for Internet-of-Things Networks," Future Internet, MDPI, vol. 12(3), pages 1-14, March.
    2. 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).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:intdis:v:14:y:2018:i:8:p:1550147718794615. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.