Source location privacy against laptop-class attacks in sensor networks

  • Authors:

  • Yi Ouyang;Zhengyi Le;Donggang Liu;James Ford;Fillia Makedon

  • Affiliations:

  • University of Texas at Arlington, Arlington, TX;University of Texas at Arlington, Arlington, TX;University of Texas at Arlington, Arlington, TX;University of Texas at Arlington, Arlington, TX;University of Texas at Arlington, Arlington, TX

  • Venue:
  • Proceedings of the 4th international conference on Security and privacy in communication netowrks
  • Year:
  • 2008

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Abstract

Sensor networks may be used in many monitoring applications where the locations of the monitored objects are quite sensitive and need to be protected. Previous research mainly focuses on protecting source location against mote-class attackers who only have a local view of the network traffic. In this paper, we focus on how to protect the source location against laptop-class attackers who have a global view of the network traffic. This paper proposes four schemes---naive, global, greedy, and probabilistic---to deal with laptop-class attacks. The naive solution uses maintenance messages sent periodically to hide real event reports. The global and greedy solutions improve the naive solution by reducing the latency of event delivery without increasing communication overhead. The probabilistic solution further improves the performance by reducing communication overhead without sacrificing location privacy. Experiments show that the probabilistic solution is practical for providing source location privacy against a laptop-class attacker.