Preserving Context Privacy in Distributed Hash Table Wireless Sensor Networks

  • Paolo PalmieriEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9543)


Wireless Sensor Networks (WSN) are often deployed in hostile or difficult scenarios, such as military battlefields and disaster recovery, where it is crucial for the network to be highly fault tolerant, scalable and decentralized. For this reason, peer-to-peer primitives such as Distributed Hash Table (DHT), which can greatly enhance the scalability and resilience of a network, are increasingly being introduced in the design of WSN’s. Securing the communication within the WSN is also imperative in hostile settings. In particular, context information, such as the network topology and the location and identity of base stations (which collect data gathered by the sensors and are a central point of failure) can be protected using traffic encryption and anonymous routing. In this paper, we propose a protocol achieving a modified version of onion routing over wireless sensor networks based on the DHT paradigm. The protocol prevents adversaries from learning the network topology using traffic analysis, and therefore p reserves the context privacy of the network. Furthermore, the proposed scheme is designed to minimize the computational burden and power usage of the nodes, through a novel partitioning scheme and route selection algorithm.


Wireless sensor networks Context privacy Anonymity Onion routing Distributed hash table 


  1. 1.
    Bloom, B.H.: Space/time trade-offs in hash coding with allowable errors. Commun. ACM 13(7), 422–426 (1970)CrossRefzbMATHGoogle Scholar
  2. 2.
    Deng, J., Han, R., Mishra, S.: Intrusion tolerance and anti-traffic analysis strategies for wireless sensor networks. In: DSN 2004, pp. 637–646. IEEE (2004)Google Scholar
  3. 3.
    Deng, J., Han, R., Mishra, S.: Decorrelating wireless sensor network traffic to inhibit traffic analysis attacks. Pervasive Mob. Comput. 2(2), 159–186 (2006)CrossRefGoogle Scholar
  4. 4.
    Dingledine, R., Mathewson, N., Syverson, P.F.: Tor: The second-generation onion router. In: USENIX 2004, pp. 303–320 (2004)Google Scholar
  5. 5.
    Fersi, G., Louati, W., Jemaa, M.B.: Distributed hash table-based routing and data management in wireless sensor networks: a survey. Wireless Netw. 19(2), 219–236 (2013)CrossRefGoogle Scholar
  6. 6.
    Gaitan, S., Calderoni, L., Palmieri, P., Veldhuis, M.C.T., Maio, D., Riemsdijk, M.B.V.: From sensing to action: quick and reliable access to information in cities vulnerable to heavy rain. IEEE Sens. J. 14(12), 4175–4184 (2014)CrossRefGoogle Scholar
  7. 7.
    Kamat, P., Zhang, Y., Trappe, W., Ozturk, C.: Enhancing source-location privacy in sensor network routing. In: ICDCS 2005, pp. 599–608. IEEE (2005)Google Scholar
  8. 8.
    Li, N., Zhang, N., Das, S.K., Thuraisingham, B.M.: Privacy preservation in wireless sensor networks: a state-of-the-art survey. Ad Hoc Netw. 7(8), 1501–1514 (2009)CrossRefGoogle Scholar
  9. 9.
    Li, Y., Thai, M.T., Wu, W. (eds.): Wireless Sensor Networks and Applications. Signals and Communication Technology. Springer, New York (2008)Google Scholar
  10. 10.
    McGoldrick, C., Clear, M., Carbajo, R.S., Fritsche, K., Huggard, M.: TinyTorrents: integrating peer-to-peer and wireless sensor networks. In: WONS 2009, pp. 109–116. IEEE (2009)Google Scholar
  11. 11.
    Palmieri, P., Pouwelse, J.: Key management for onion routing in a true peer to peer setting. In: Yoshida, M., Mouri, K. (eds.) IWSEC 2014. LNCS, vol. 8639, pp. 62–71. Springer, Heidelberg (2014)Google Scholar
  12. 12.
    Syverson, P.F., Goldschlag, D.M., Reed, M.G.: Anonymous connections and onion routing. In: IEEE Symposium on Security and Privacy 1997, pp. 44–54. IEEE (1997)Google Scholar
  13. 13.
    Xi, Y., Schwiebert, L., Shi, W.: Preserving source location privacy in monitoring-based wireless sensor networks. In: IPDPS 2006, IEEE (2006)Google Scholar
  14. 14.
    Yang, Y., Shao, M., Zhu, S., Urgaonkar, B., Cao, G.: Towards event source unobservability with minimum network traffic in sensor networks. In: WISEC 2008. pp. 77–88. ACM (2008)Google Scholar
  15. 15.
    Zhang, L.: A self-adjusting directed random walk approach for enhancing source-location privacy in sensor network routing. In: IWCMC 2006, pp. 33–38. ACM (2006)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Computing and InformaticsBournemouth UniversityPooleUK

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