Performance Based Location Privacy in Sensor Networks against a Global Eaves Dropper.

Existing techniques defend the leakage of location information from a limited adversary who can only observe network traffic in a short region. However, an energetic attacker, the global eavesdropper, is realistic and can defeat these existing techniques. This proposal 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 project then proposes two approach to provide location privacy to monitored objects (source-location privacy)?periodic collection and source simulation?and two approach to provide location privacy to data sinks (sink-location privacy)?sink simulation and backbone flooding. These procedures provide understanding between privacy, communication outlay, and latency. Through investigation and simulation, it is scheduled to demonstrate that the proposed techniques are efficient and effective for source and sink-location privacy in sensor networks.