IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v73y2020i3d10.1007_s11235-019-00616-1.html
   My bibliography  Save this article

Toward an integrated dynamic defense system for strategic detecting attacks in cloud networks using stochastic game

Author

Listed:
  • El Mehdi Kandoussi

    (Hassan 1st University)

  • Mohamed Hanini

    (Hassan 1st University)

  • Iman Mir

    (University Abdelmalek Essaadi)

  • Abdelkrim Haqiq

    (Hassan 1st University)

Abstract

In a complex network as a cloud computing environment, security is becoming increasingly based on deception techniques. To date, the static nature of cyber networks offers to adversaries good opportunities to systematically study the network environment, launch a cyber-attack effortlessly and wide-spread and finally defeat the target system. In order to resolve the limitations of the traditional security measures as intrusion prevention or detection systems, firewall, access list, etc., which did not change the attack surface and cannot avoid zero-days attacks, technics that provide dynamic defense, such virtual machine migration and honeypot should be deployed. Despite this, with a virtual machine migration technique, not all virtual machines’ migration between servers enhances security considerably. In this paper, we propose an integrated defense system combining virtual machine migration and honeypot. The effectiveness of the proposed system is discussed in terms of security policies. In addition, our proposed model determines the potential attack paths quantitatively then classifies them into two sub-sets: attack paths explored only and attack paths explored and exploited based on the black box intrusion steps. Thus, to model the interaction attacker–defender, the attack graph combined with the stochastic game theory is used. Finally, we carry out some numerical results to demonstrate the effectiveness of the proposed security game model.

Suggested Citation

  • El Mehdi Kandoussi & Mohamed Hanini & Iman Mir & Abdelkrim Haqiq, 2020. "Toward an integrated dynamic defense system for strategic detecting attacks in cloud networks using stochastic game," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 73(3), pages 397-417, March.
  • Handle: RePEc:spr:telsys:v:73:y:2020:i:3:d:10.1007_s11235-019-00616-1
    DOI: 10.1007/s11235-019-00616-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-019-00616-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11235-019-00616-1?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jin-Hee Cho & Noam Ben-Asher, 2018. "Cyber defense in breadth: Modeling and analysis of integrated defense systems," The Journal of Defense Modeling and Simulation, , vol. 15(2), pages 147-160, April.
    2. Ammar Boulaiche & Kamel Adi, 2018. "An auto-learning approach for network intrusion detection," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 68(2), pages 277-294, June.
    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:spr:telsys:v:73:y:2020:i:3:d:10.1007_s11235-019-00616-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.