Location privacy is very important, especially in hostile environments. Failure to protect such information can completely subvert the intended purposes of sensor network applications. A number of privacy-preserving routing techniques have been developed for sensor networks. However, most of them are designed to protect against an adversary only capable of eavesdropping on a limited portion of the network at a time. This paper first formalizes the location privacy issues in sensor networks under this strong adversary model and computes a lower bound on the communication overhead needed for achieving a given level of location privacy. The paper then proposes two techniques to provide location privacy to monitored objects (source-location privacy)—periodic collection and source simulation—and two techniques to provide location privacy to data sinks (sink-location privacy)—sink simulation and backbone flooding. These techniques provide trade-offs between privacy, communication cost, and latency.
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