IDEAS home Printed from https://ideas.repec.org/a/igg/jisp00/v14y2020i4p42-56.html
   My bibliography  Save this article

A Confidence Interval Based Filtering Against DDoS Attack in Cloud Environment: A Confidence Interval Against DDoS Attack in the Cloud

Author

Listed:
  • Mohamed Haddadi

    (Département d'Informatique, Faculté des Sciences Exactes, Université de Bejaia, Bejaia, Algeria)

  • Rachid Beghdad

    (Département d'Informatique, Faculté des Sciences Exactes, Université de Bejaia, Bejaia, Algeria)

Abstract

Distributed denial of service (DDoS) attacks have become a serious danger against the availability of services in cloud computing environment. Current defending mechanisms cannot detect DDoS attacks with high accuracy. This is mainly due to the fact that the unrealistic value of the studied variables was used. In view of this problem, the authors propose a novel approach called confidence interval-based filtering (CIF) to detect DDoS attacks. The proposed approach is implemented using VMware and JAVA applications. The simulation results showed that CIF outperforms the existing approaches in terms of detection rate and false negative and positive rates with an acceptable computation time.

Suggested Citation

  • Mohamed Haddadi & Rachid Beghdad, 2020. "A Confidence Interval Based Filtering Against DDoS Attack in Cloud Environment: A Confidence Interval Against DDoS Attack in the Cloud," International Journal of Information Security and Privacy (IJISP), IGI Global, vol. 14(4), pages 42-56, October.
  • Handle: RePEc:igg:jisp00:v:14:y:2020:i:4:p:42-56
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJISP.2020100103
    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:14:y:2020:i:4:p:42-56. 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.