Providing Destination-Location Privacy in Wireless Sensor Network Using Bubble Routing

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 202)


One of the most challenging problems for wireless sensor networks (WSNs) is in how to provide adequate location privacy. In this paper, we will address the concern to adequately provide routing-based destination-location privacy (DLP). The privacy of the location of the destination sensor node is critical and highly vulnerable by the usage of wireless communications. While message content privacy can be accomplished through message encryption, it is much more difficult to adequately address the location privacy. For WSNs, destination-location privacy service is further complex by the fact that sensors consist of low-cost and energy efficient radio devices. Therefore, using computationally intensive cryptographic algorithms (such as public-key cryptosystems) and large scale broadcasting-based protocols are not suitable for WSNs. We propose a unique routing technique that can provide strong destination-location privacy with low tradeoff in the energy overhead. In our proposed scheme, the source node randomly selects an intermediate node from pre-determined region located around the destination node, which we refer to as the bubble region. The bubble region would be large enough to make it infeasible for an adversary to monitor the entire area. Also, in this scheme, we will mix real messages with fake messages to add to the security strength in providing destination-location privacy. We compare our proposed scheme to other well known schemes.


Destination location privacy Wireless sensor networks Energy efficiency Bubble region 


  1. 1.
    Chaum D (1981) Untraceable electronic mail, return addresses, and digital pseudonyms. Commun ACM 24:84–90Google Scholar
  2. 2.
    Chaum D (1988) The dinning cryptographer problem: unconditional sender and recipient untraceability. J Cryptol 1(1):65–75MathSciNetMATHCrossRefGoogle Scholar
  3. 3.
    von Ahn L, Bortz A, Hopper N (2003) k-anonymous message transmission. In: Proceedings of CCS, Washington DC, pp 122–130Google Scholar
  4. 4.
    Beimel A, Dolev S (2003) Buses for anonymous message delivery. J Cryptol 16:25–39MathSciNetMATHCrossRefGoogle Scholar
  5. 5.
    Golle P, Juels A (2004) Dining cryptographers revisited. In: Advances in cryptology – Eurocrypt 2004. Lecture notes in computer science, vol 3027. Springer, Berlin, pp 456–473Google Scholar
  6. 6.
    Goel S, Robson M, Polte M, Sirer E (2003) Herbivore: a scalable and efficient protocol for anonymous communication, Tech. Rep. 2003–1890, Cornell University, IthacaGoogle Scholar
  7. 7.
    Reed M, Syverson P, Goldschlag D (1998) Anonymous connections and onion routing. IEEE J Sel Areas Commun 16(4):482–494CrossRefGoogle Scholar
  8. 8.
    Reiter, M, Rubin A (1998) Crowds: anonymity for web transaction. ACM Trans Inf Syst Secur 1(1):66–92CrossRefGoogle Scholar
  9. 9.
    Deng J, Han R, Mishra S (2004) Intrusion tolerance and anti-traffic analysis strategies for wireless sensor networks. In: DSN ’04: proceedings of the 2004 international conference on dependable systems and networks, Washington, DC. IEEE Computer Society, p 637Google Scholar
  10. 10.
    Deng J, Han R, Mishra S (2005) Countermeasures against traffic analysis attacks in wireless sensor networks. In: First international conference on security and privacy for emerging areas in communications networks, 2005. SecureComm 2005, Athens, pp 113–126Google Scholar
  11. 11.
    Jian Y, Chen S, Zhang Z, Zhang L (2007) Protecting recieiver-location privacy in wireless sensor networks. In: INFOCOM 2007. Twenty-six annual joint conference of the IEEE computer and communications societies. IEEE, Piscataway, pp 1955–1963Google Scholar
  12. 12.
    Yang Y, Shao M, Zhu S, Urgaonkar B, Cao G (2008) Towards event source unobservability with minimum network traffic in sensor networks. In: WiSec ’08: Proceedings of the first ACM conference on wireless network security. ACM, New York, pp 77–88Google Scholar
  13. 13.
    Shao M, Yang Y, Zhu S, Cao G (2008) Towards statistically strong source anonymity for sensor networks. In: INFOCOM 2008. The 27th conference on Computer Communications. IEEE. IEEE, Piscataway, pp 51–55Google Scholar
  14. 14.
    Kamat P, Zhang Y, Trappe W, Ozturk C (2005) Enhancing source-location privacy in sensor network routing. In: 25th IEEE international conference on distributed computing systems, 2005. ICDCS 2005. Proceedings, Columbus, pp 599–608Google Scholar
  15. 15.
    Ozturk C, Zhang Y, Trappe W (2004) Source-location privacy in energy-constrained sensor network routing. In: SASN ’04: Proceedings of the 2nd ACM workshop on security of ad hoc and sensor networks. ACM, New York, pp 88–93Google Scholar
  16. 16.
    Xi Y, Schwiebert L, Shi W (2006) Preserving source location privacy in monitoring-based wireless sensor networks. In: IPDPS. IEEE, PiscatawayGoogle Scholar
  17. 17.
    Gülcü C, Tsudik G (1996) Mixing email with babel. In: Proceedings of the symposium on network and distributed system security, San DiegoGoogle Scholar
  18. 18.
    Möller U, Cottrell L, Palfrader P, Sassaman L (2003) Mixmaster protocol. Version 2Google Scholar
  19. 19.
    Ye M, Li C, Chen G, Wu J (2005) Eecs: an energy efficient clustering scheme in wireless sensor networks. In: Performance, computing, and communications conference, 2005. IPCCC 2005. 24th IEEE International, Phoenix, pp 535–540Google Scholar
  20. 20.
    Heinzelman WB (2000) Application-specific protocol architectures for wireless networks. Ph.D. thesis. Supervisor-Anantha P. Chandrakasan and Supervisor-Hari BalakrishnanGoogle Scholar
  21. 21.
    Neander J, Hansen E, Nolin M, Bjorkman M (2006) Asymmetric multihop communication in large sensor networks. In: 1st international symposium on wireless pervasive computing, 2006, Phuket, pp 7Google Scholar
  22. 22.
    Younis O, Fahmy S (2004) Heed: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans Mob Comput 3:366–379CrossRefGoogle Scholar
  23. 23.
    Zhang Y, Liu W, Fang Y, Wu D (2006) Secure localization and authentication in ultra-wideband sensor networks. IEEE J Sel Areas in Commun 24:829–835CrossRefGoogle Scholar
  24. 24.
    Cheng X, Thaeler A, Xue G, Chen D (2004) Tps: a time-based positioning scheme for outdoor wireless sensor networks. In: INFOCOM 2004. Twenty-third annual joint conference of the IEEE computer and communications societies, Hong Kong, vol 4, pp 2685–2696Google Scholar
  25. 25.
    Chan H, Perrig A (2005) Pike: peer intermediaries for key establishment in sensor networks. In: INFOCOM 2005. 24th annual joint conference of the IEEE computer and communications societies. Proceedings IEEE, Miami, vol 1, pp 524–535Google Scholar
  26. 26.
    Perrig A, Szewczyk R, Wen V, Culler D, Tygar J (2001) SPINS: security protocols for sensor networks. In: Seventh annual international conference on mobile computing and networks (MobiCOM 2001), RomeGoogle Scholar
  27. 27.
    Traynor P, Kumar R, Choi H, Cao G, Zhu S, La Porta T (2007) Efficient hybrid security mechanisms for heterogeneous sensor networks. IEEE Trans Mob Comput 6:663–677CrossRefGoogle Scholar
  28. 28.
    Zhu S, Setia S, Jajodia S (2003) Leap: efficient security mechanisms for large-scale distributed sensor networks. In: CCS ’03: proceedings of the 10th ACM conference on computer and communications security. ACM, New York, pp 62–72Google Scholar
  29. 29.
    Hill J, Szewczyk R, Woo SHA, Culler D, Pister K (2000) System architecture directions for networked sensors. In: Proceedings of ACM ASPLOS IX, CambridgeGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringMichigan State UniversityEast LansingUSA

Personalised recommendations