Advertisement

Protecting Source Location Privacy in Wireless Sensor Networks with Data Aggregation

  • Wenbo Yang
  • Wen Tao Zhu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6406)

Abstract

Many efforts have been made to protect sensor networks against attacks, and standard mechanisms such as encryption are widely used to provide security services. However, the wireless transmission of a message itself may reveal to the adversary the origin of a sensed event, i.e., the source location of the message. Providing such position privacy in sensor networks is a challenging task. Traditional anonymity techniques are inappropriate for resource-constrained sensor networks, but an adversary may easily monitor the network communications. In this work, we focus on protecting source location privacy in the global attack model, where an adversary may have a global view of the communications in a sensor network and employ traffic analysis to locate the message sources. A flexible and effective countermeasure based on secure data aggregation is proposed to prevent the leakage of source location information. Both theoretical analysis and simulations are presented to validate the proposed scheme.

Keywords

Wireless sensor networks information security location privacy anonymity data aggregation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Ozturk, C., Zhang, Y., Trappe, W.: Source-location privacy in energy-constrained sensor network routing. In: Proc. 2nd ACM workshop on Security of Ad hoc and Sensor Networks, pp. 88–93 (2004)Google Scholar
  2. 2.
    Li, N., Zhang, N., Das, S.K., Thuraisingham, B.: Privacy preservation in wireless sensor networks: a state-of-the-art survey. Ad. Hoc. Netw. 7(8), 1501–1514 (2009)CrossRefGoogle Scholar
  3. 3.
    Kamat, P., Zhang, Y., Trappe, W., Ozturk, C.: Enhancing source-location privacy in sensor network routing. In: Proc. 25th IEEE International Conference on Distributed Computing Systems, pp. 599–608 (2005)Google Scholar
  4. 4.
    Xi, Y., Schwiebert, L., Shi, W.: Preserving source location privacy in monitoring-based wireless sensor networks. In: Proc. 20th International Parallel and Distributed Processing Symposium, pp. 425–432 (2006)Google Scholar
  5. 5.
    Ouyang, Y., Le, X., Chen, G., Ford, J., Makedon, F.: Entrapping adversaries for source protection in sensor networks. In: Proc. International Symposium on a World of Wireless, Mobile and Multimedia Networks, pp. 10–34 (2006)Google Scholar
  6. 6.
    Yang, Y., Shao, M., Zhu, S., Urgaonkar, B., Cao, G.: Towards event source unobservability with minimum network traffic in sensor networks. In: Proc. 1st ACM Conference on Wireless Network Security, pp. 77–88 (2008)Google Scholar
  7. 7.
    Mehta, K., Liu, D., Wright, M.: Location privacy in sensor networks against a global eavesdropper. In: Proc. IEEE International Conference on Network Protocols, pp. 314–323 (2007)Google Scholar
  8. 8.
    Shao, M., Yang, Y., Zhu, S., Cao, G.: Towards statistically strong source anonymity for sensor networks. In: Proc. 27th IEEE International Conference on Computer Communications, pp. 466–474 (2008)Google Scholar
  9. 9.
    Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensor networks. In: Proc. 33rd Hawaii International Conference on System Sciences, pp. 3005–3014 (2000)Google Scholar
  10. 10.
    Younis, O., Fahmy, S.: HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans. on Mob. Comput. 3(4), 366–379 (2004)CrossRefGoogle Scholar
  11. 11.
    He, W., Liu, X., Nguyen, H., Nahrstedt, K., Abdelzaher, T.T.: PDA: Privacy-preserving data aggregation in wireless sensor networks. In: Proc. 26th IEEE International Conference on Computer Communications, pp. 2045–2053 (2007)Google Scholar
  12. 12.
    Madden, S., Franklin, M.J., Hellerstein, J.M., Hong, W.: TAG: A tiny aggregation service for ad-hoc sensor networks. In: Proc. 5th Symposium on Operating Systems Design and Implementation, pp. 131–146 (2002)Google Scholar
  13. 13.
    Knuth, D.E.: 3.4. In: The Art of Computer Programming, 3rd edn. Seminumerical Algorithms, vol. 2, pp. 132–133. Addison Wesley Longman, Amsterdam (1998)Google Scholar
  14. 14.
    Feng, T., Wang, C., Zhang, W., Ruan, L.: Confidentiality protection for distributed sensor data aggregation. In: Proc. 27th IEEE International Conference on Computer Communications, pp. 475–483 (2008)Google Scholar
  15. 15.
    Castelluccia, C., Chan, A.C.F., Mykletun, E., Tsudik, G.: Efficient and provably secure aggregation of encrypted data in wireless sensor networks. ACM Trans. on Sens. Netw. 5(3), 1–36 (2009)CrossRefGoogle Scholar
  16. 16.
    Wolff, R.W.: Possion arrivals see time averages. Operations Research 30(2), 223–231 (1982)MathSciNetCrossRefzbMATHGoogle Scholar
  17. 17.
    Mood, A.M., Graybill, F.A., Boes, D.C.: 5.3.2. In: Introduction to The Theory of Statistics, pp. 182–185. McGraw-Hill, New York (1974)Google Scholar
  18. 18.
    Kleinrock, L.: Queueing Systems. Theory, vol. 1. John Wiley and Sons, Inc., Chichester (1975)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Wenbo Yang
    • 1
  • Wen Tao Zhu
    • 1
  1. 1.State Key Laboratory of Information SecurityGraduate University of Chinese Academy of SciencesBeijingP.R. China

Personalised recommendations