IDEAS home Printed from https://ideas.repec.org/a/igg/jisp00/v11y2017i1p18-34.html
   My bibliography  Save this article

A New Meta-Heuristics for Intrusion Detection System Inspired from the Protection System of Social Bees

Author

Listed:
  • Mohamed Amine Boudia

    (Dr. Moulay Tahar University of Saida, Saida, Algeria)

  • Reda Mohamed Hamou

    (GeCoDe Laboratory, Department of Computer Science, Dr. Moulay Tahar University of Saida, Saida, Algeria)

  • Abdelmalek Amine

    (GeCoDe Laboratory, Department of Computer Science, Dr. Moulay Tahar University of Saida, Saida, Algeria)

Abstract

In this paper, the authors will propose a meta-heuristic for intrusion detection system by scenario, inspired from the protection system of social bees to their hive. This approach is based on a specialized multi agent system where the authors will give a limited responsibility to each guard bee agent: to secure only one port, this specialization aims to better exploit the training set and the hardware and software performance. The authors will start this paper by a short introduction where they will show the importance of IT security especially today, then they will give a little insight into the state of the art, before starting the essential part of a scientific paper: “our approach” where the authors will explain the natural model, and then they'll simplify their model in a modelling table to share their vision and philosophy to switch from natural model to artificial model, and then they will detail the artificial model they are going to experience in the next chapter, they will discuss the results and make comparison in the two following chapter to get out with a conclusion and perspective of their future work.

Suggested Citation

  • Mohamed Amine Boudia & Reda Mohamed Hamou & Abdelmalek Amine, 2017. "A New Meta-Heuristics for Intrusion Detection System Inspired from the Protection System of Social Bees," International Journal of Information Security and Privacy (IJISP), IGI Global, vol. 11(1), pages 18-34, January.
  • Handle: RePEc:igg:jisp00:v:11:y:2017:i:1:p:18-34
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJISP.2017010102
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:igg:jisp00:v:11:y:2017:i:1:p:18-34. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.