IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v18y2022i3p15501329221077922.html
   My bibliography  Save this article

An intrusion detection mechanism for IPv6-based wireless sensor networks

Author

Listed:
  • Min Wei
  • Chunmeng Rong
  • Erxiong Liang
  • Yuan Zhuang

Abstract

With the advancement of IPv6 technology, many nodes in wireless sensor networks realize seamless connections with the Internet via IPv6 addresses. Security issues are a significant obstacle to the widespread adoption of IPv6 technology. Resource-constrained IPv6 nodes face dual attacks: local and Internet-based. Moreover, constructing an active cyber defense system for IPv6-based wireless sensor networks is difficult. In this article, we propose a K -nearest neighbor-based intrusion detection mechanism and design a secure network framework. This mechanism trains an intrusion detection algorithm using a feature data set to create a normal profile. The intrusion detection algorithm uses the normal profile to perform real-time detection of network traffic data to achieve rapid detections connecting many devices in a wireless sensor network. In addition, we develop a test platform to verify this mechanism. Experimental results show that this mechanism is appropriate for IPv6-based wireless sensor networks and achieves a low false-positive rate and good intrusion detection accuracy at an acceptable resource cost.

Suggested Citation

  • Min Wei & Chunmeng Rong & Erxiong Liang & Yuan Zhuang, 2022. "An intrusion detection mechanism for IPv6-based wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 18(3), pages 15501329221, March.
    • Handle: RePEc:sae:intdis:v:18:y:2022:i:3:p:15501329221077922
    DOI: 10.1177/15501329221077922
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/15501329221077922
    Download Restriction: no
    File URL: https://libkey.io/10.1177/15501329221077922?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
    ---><---

    References listed on IDEAS

    as
    1. Hong Zhang & Shigen Shen & Qiying Cao & Xiaojun Wu & Shaofeng Liu, 2020. "Modeling and analyzing malware diffusion in wireless sensor networks based on cellular automaton," International Journal of Distributed Sensor Networks, , vol. 16(11), pages 15501477209, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      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:18:y:2022:i:3:p:15501329221077922. 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.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.