• DocumentCode
    153886
  • Title

    CR-Honeynet: A Learning & Decoy Based Sustenance Mechanism against Jamming Attack in CRN

  • Author

    Bhunia, Swarup ; Sengupta, Sabyasachi ; Vazquez-Abad, Felisa

  • Author_Institution
    Univ. of Nevada, Reno, NV, USA
  • fYear
    2014
  • fDate
    6-8 Oct. 2014
  • Firstpage
    1173
  • Lastpage
    1180
  • Abstract
    Cognitive Radio Network (CRN) enables secondary users to borrow unused spectrum from the proprietary users in a dynamic and opportunistic manner. However, dynamic and open access nature of available spectrum brings a serious challenge of sustenance amongst CRNs which makes them vulnerable to various spectrum etiquette attacks. Jamming-based denial of service (DoS) attack poses serious threats to legitimate communications and packet delivery. A rational attacker targets certain transmission characteristics to find the highest impacting communication of CRN and causes maximum disruption. In this paper, inspired by the honey pot concept in cyber crime, we propose a honey net based defense mechanism, which aims to deter the attacker from jamming legitimate communications. The honey net passively learns the attacker´s strategy from the past history of attacks and actively adapts pre-emptive decoy mechanisms to prevent attacks on legitimate communications. Simulation results show that the with help of honey net mechanism, CRN successfully avoids jamming attacks and thereby improves system performance in terms of packet delivery ratio.
  • Keywords
    cognitive radio; jamming; spread spectrum communication; CR-Honeynet; Honeynet based defense mechanism; cognitive radio network; cyber crime; jamming attack; jamming-based denial of service attack; packet delivery; rational attacker; sustenance mechanism; Delays; Hidden Markov models; Jamming; Monitoring; Probes; Sensors; Switches; Cognitive Radio; Honeynet; Jamming; Stochastic Learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Military Communications Conference (MILCOM), 2014 IEEE
  • Conference_Location
    Baltimore, MD
  • Type

    conf

  • DOI
    10.1109/MILCOM.2014.197
  • Filename
    6956917