Reputation-Based Trust Management for Distributed Spectrum Sensing

  • Seamus Mc Gonigle
  • Qian Wang
  • Meng Wang
  • Adam Taylor
  • Eamonn O. NuallainEmail author
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 284)


One of the solutions to the hidden node problem in Cognitive Radio (CR) networks is to construct a global radio environment map (REM) hosted on a central controlling server. With this approach, the responsibility of sensing the radio environment can be distributed among all the nodes in the cognitive radio network. This introduces vulnerability because the server depends on the participating nodes to provide honest and accurate spectrum sense information. This research develops a reputation-based security mechanism that protects the radio environment map against falsified spectrum information that may be provided by malicious members of the network.


Cognitive Radio Secondary User Cognitive Radio Network Malicious Node Trust Management 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    E.O. Nuallain, A proposed propagation-based methodology with which to address the hidden node problem and security/reliability issues in cognitive radio, in Wireless Communications, Networking and Mobile Computing, 2008. WiCOM'08. 4th International Conference on Wireless Communications, Networking and Mobile Computing (IEEE, 2008), Dalian, China, pp. 1–5Google Scholar
  2. 2.
    Y. Zhao, D. Raymond, C. da Silva, J.H. Reed, S.F. Midkiff, Performance evaluation of radio environment map-enabled cognitive spectrum-sharing networks. in Military Communications Conference, 2007. MILCOM 2007. IEEE (IEEE, 2007), Orlando, Florida, pp. 1–7Google Scholar
  3. 3.
    R. Chen, J.M. Park, Y.T. Hou, J.H. Reed, Toward secure distributed spectrum sensing in cognitive radio networks. Commun. Mag. IEEE 46(4), 50–55 (2008)CrossRefGoogle Scholar
  4. 4.
    J.O. Kephart, D.M. Chess, The vision of autonomic computing. Computer 36(1), 41–50 (2003)CrossRefMathSciNetGoogle Scholar
  5. 5.
    B. Schneier, Liars and Outliers: Enabling the Trust that Society Needs to Thrive (Wiley, Indianapolis, 2012)Google Scholar
  6. 6.
    New Scientist, Wireless spectrum: a hidden natural resource (2009),
  7. 7.
    K.R. Liu, B. Wang, Cognitive Radio Networking and Security: A Game-Theoretic View (Cambridge University Press, Cambridge, MA, 2010)CrossRefGoogle Scholar
  8. 8.
    S. Parvin, F.K. Hussain, Trust-based security for community-based cognitive radio networks. in Advanced Information Networking and Applications (AINA), 2012 I.E. 26th International Conference on (IEEE, 2012), Fukuoka, Japan, pp. 518–525Google Scholar
  9. 9.
    T.C. Clancy, N. Goergen, Security in cognitive radio networks: threats and mitigation. in Cognitive Radio Oriented Wireless Networks and Communications, 2008. CrownCom 2008. 3rd International Conference on (IEEE, 2008), Singapore, pp. 1–8Google Scholar
  10. 10.
    Q.H. Mahmoud, Cognitive Networks (Wiley, 2007), Chichester, West Sussex, pp. 57–71Google Scholar
  11. 11.
    A. Jøsang, R. Ismail, C. Boyd, A survey of trust and reputation systems for online service provision. Decis. Support Syst. 43(2), 618–644 (2007)CrossRefGoogle Scholar
  12. 12.
    K. Zeng, P. Paweczak, D. Cabric, Reputation-based cooperative spectrum sensing with trusted node’s assistance. Commun. Lett. IEEE 14(3), 226–228 (2010)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Seamus Mc Gonigle
    • 1
  • Qian Wang
    • 1
  • Meng Wang
    • 1
  • Adam Taylor
    • 1
  • Eamonn O. Nuallain
    • 1
    Email author
  1. 1.School of Computer Science and StatisticsTrinity College DublinDublinIreland

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