IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v23y2021i4d10.1007_s10796-020-10087-4.html
   My bibliography  Save this article

Decepticon: a Theoretical Framework to Counter Advanced Persistent Threats

Author

Listed:
  • Rudra P. Baksi

    (University at Buffalo, SUNY)

  • Shambhu J. Upadhyaya

    (University at Buffalo, SUNY)

Abstract

Deception has been proposed in the literature as an effective defense mechanism to address Advanced Persistent Threats (APT). However, administering deception in a cost-effective manner requires a good understanding of the attack landscape. The attacks mounted by APT groups are highly diverse and sophisticated in nature and can render traditional signature based intrusion detection systems useless. This necessitates the development of behavior oriented defense mechanisms. In this paper, we develop Decepticon (Deception-based countermeasure), a Hidden Markov Model based framework where the indicators of compromise (IoC) are used as the observable features to aid in detection. This theoretical framework also includes several models to represent the spread of APTs in a computer system. The presented framework can be used to select an appropriate deception script when faced with APTs or other similar malware and trigger an appropriate defensive response. The effectiveness of the models in a networked system is illustrated by considering a real APT type ransomware.

Suggested Citation

  • Rudra P. Baksi & Shambhu J. Upadhyaya, 2021. "Decepticon: a Theoretical Framework to Counter Advanced Persistent Threats," Information Systems Frontiers, Springer, vol. 23(4), pages 897-913, August.
  • Handle: RePEc:spr:infosf:v:23:y:2021:i:4:d:10.1007_s10796-020-10087-4
    DOI: 10.1007/s10796-020-10087-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-020-10087-4
    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/s10796-020-10087-4?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. Boldizsár Bencsáth & Gábor Pék & Levente Buttyán & Márk Félegyházi, 2012. "The Cousins of Stuxnet: Duqu, Flame, and Gauss," Future Internet, MDPI, vol. 4(4), pages 1-33, November.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Sanjay K. Sahay & Nihita Goel & Murtuza Jadliwala & Shambhu Upadhyaya, 2021. "Advances in Secure Knowledge Management in the Artificial Intelligence Era," Information Systems Frontiers, Springer, vol. 23(4), pages 807-810, August.

    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.
    1. Kumar, Rajesh & Kela, Rohan & Singh, Siddhant & Trujillo-Rasua, Rolando, 2022. "APT attacks on industrial control systems: A tale of three incidents," International Journal of Critical Infrastructure Protection, Elsevier, vol. 37(C).
    2. Mohd Nor Akmal Khalid & Amjed Ahmed Al-Kadhimi & Manmeet Mahinderjit Singh, 2023. "Recent Developments in Game-Theory Approaches for the Detection and Defense against Advanced Persistent Threats (APTs): A Systematic Review," Mathematics, MDPI, vol. 11(6), pages 1-34, March.

    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:infosf:v:23:y:2021:i:4:d:10.1007_s10796-020-10087-4. 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.