Protecting Source and Sink Location Privacy in Sensor Networks

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.