Source Location Privacy against Laptop-Class Attacks in Sensor Networks

Sensor networks may be used in many monitoring applica- tions 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 at- tackers who only have a local view of the network traffic. In this paper, we focus on how to protect the source loca- tion 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 mes- sages 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 communica- tion overhead. The probabilistic solution further improves the performance by reducing communication overhead with- out sacrificing location privacy. Experiments show that the probabilistic solution is practical for providing source loca- tion privacy against a laptop-class attacker.