Location armoring in sensor network using virtual objects

In sensor network, it is relatively easy for an adversary to eavesdrop and trace packet movement in the network in order to capture the location information. After studying the adversary's behaviour patterns, we present certain steps to prevent this problem. Many protocols for sensor network security provide confidentiality for the content of secret information which usually remains exposed. Such information can be exploited by an adversary to derive sensitive information such as the locations of monitored objects and data sinks in the field. Encounters on these components can significantly undermine any network application. Offered techniques defend the leakage of location information from a partial adversary who can only observe network traffic in a small field. However, a stronger adversary is realistic and can defeat these obtainable techniques. 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 techniques to provide location privacy to source-location and data sinks. These techniques provide trade-offs between solitude, communication cost, and latency. We demonstrate that the anticipated techniques are efficient and effective for source and sink-location privacy in sensor networks by the analysis.