Distributed Data Fusion for Detecting Sybil Attacks in VANETs

  • Nicole El Zoghby
  • Véronique Cherfaoui
  • Bertrand Ducourthial
  • Thierry Denœux
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 164)

Abstract

Sybil attacks have become a serious threat as they can affect the functionality of VANETs (Vehicular Ad Hoc Networks). This paper presents a method for detecting such attacks in VANETs based on distributed data fusion. An algorithm has been developed in order to build distributed confidence over the network under the belief function framework. Our approach has been validated by simulation.

Keywords

Malicious Node Belief Function Vehicular Network Public Knowledge Unit Disk Graph 
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.

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References

  1. 1.
    Singh, M.P., Yu, B.: An evidential model of distributed reputation management. In: First international Joint Conference on Autonomous Agents and Multi-Agents Systems, Bologna, Italy, pp. 294–301. ACM Press (2002)Google Scholar
  2. 2.
    Chen, T.M., Venkataramanan, V.: Dempster-shafer theory for intrusion detection in ad hoc networks. IEEE Internet Computing 9, 35–41 (2005)CrossRefGoogle Scholar
  3. 3.
    Cherfaoui, V., Denoeux, T., Cherfi, Z.L.: Distributed data fusion: application to confidence management in vehicular networks. In: 11th Int. Conf. on Information Fusion, Germany, pp. 846–853 (2008)Google Scholar
  4. 4.
    Dempster, A.P.: Upper and lower probabilities induced by a multivalued mapping. Annals of Mathematical Statistics 38, 325–339 (1967)MathSciNetMATHCrossRefGoogle Scholar
  5. 5.
    Denoeux, T.: Conjunctive and disjunctive combination of belief functions induced by nondistinct bodies of evidence. Artificial Intelligence 172, 234–264 (2008)MathSciNetMATHCrossRefGoogle Scholar
  6. 6.
    Douceur, J.R.: The sybil attack. In: The International Workshop on Peer to Peer Systems, Cambridge, MA, USA, pp. 251–260 (2002)Google Scholar
  7. 7.
    Golle, P., Greene, D., Staddon, J.: Detecting and correcting malicious data in vanets. In: 1st ACM Workshop on Vehicular Ad hoc Networks (VANET), New York, NY, USA, pp. 29–37 (2004)Google Scholar
  8. 8.
    Guette, G., Ducourthial, B.: On the sybil attack detection in vanet. In: International Workshop on Mobile Vehicular Networks (MoveNet 2007), co-located with IEEE MASS 2007, Pisa (October 2007)Google Scholar
  9. 9.
    Liu, J., Issarny, V.: Enhanced reputation mechanism for mobile ad hoc networks. In: 2nd International Conference on Trust Management, Oxford, UK, pp. 48–62 (2004)Google Scholar
  10. 10.
    Lochert, C., Scheuermann, B., Mauve, M.: Probabilistic aggregation for data dissemination in vanets. In: 4th ACM international Workshop on Vehicular Ad Hoc Networks, Montreal, QC, Canada, pp. 1–8 (2007)Google Scholar
  11. 11.
    Mitchell, H.B.: Multisensor Data Fusion: An introduction. Springer (2007)Google Scholar
  12. 12.
    Piro, C., Shields, C., Levine, B.N.: Detecting the sybil attack in mobile ad hoc networks. In: IEEE/ACM Intl Conf on Security and privacy in Communication Networks (SecureComm), pp. 1–11 (August 2006)Google Scholar
  13. 13.
    Raya, M., Papadimitratos, P., Gligor, V.D., Hubaux, J.-P.: On data-centric trust establishment in ephemeral ad hoc networks. In: The 28th IEEE Conference on Computer Communications (INFOCOM), Phoenix, AZ, USA, pp. 1238–1246 (April 2008)Google Scholar
  14. 14.
    Evans, R.J., Mclaughlin, S., Krishnamurthy, V.: Bayesian network model for data incest in a distributed sensor network. In: The 7th International Conference on Information Fusion, Stockholm, Sweden, vol. 1 (2004)Google Scholar
  15. 15.
    Smets, P.: Belief functions: the disjunctive rule of combination and the generalized Bayesian theorem. International Journal of Approximate Reasoning 9, 1–35 (1993)MathSciNetMATHCrossRefGoogle Scholar
  16. 16.
    Theodorakopoulos, G., Baras, J.S.: Trust evaluation in ad-hoc networks. In: ACM Workshop Wireless Security, Philadelphia, PA, USA, pp. 1–10 (2004)Google Scholar
  17. 17.
    Wang, J., Sun, H.-J.: A new evidential trust model for open communities. Computer Standards & Interfaces 31, 994–1001 (2009)CrossRefGoogle Scholar
  18. 18.
    Xiao, B., Yu, B., Gao, C.: Detection and localization of sybil nodes in vanets. In: The Workshop on Dependability Issues in Wireless Ad Hoc Networks and Sensor Networks, Los Angeles, CA, USA, pp. 1–8 (2006)Google Scholar
  19. 19.
    Yan, G., Choudhary, G., Weigle, M., Olariu, S.: Providing vanet security through active position detection. Computer Communications: Special Issue on Mobility Protocols for ITS/ VANET 31(12), 2883–2897 (2008)Google Scholar
  20. 20.
    Zacharia, G., Maes, P.: Trust management through reputation mechanisms. Applied Artificial Intelligence 14, 881–907 (2000)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Nicole El Zoghby
    • 1
  • Véronique Cherfaoui
    • 1
  • Bertrand Ducourthial
    • 1
  • Thierry Denœux
    • 1
  1. 1.Heudiasyc UMR CNRS 7253Université de Technologie de CompiègneCompiègneFrance

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