Title: "STATISTICAL FRAMEWORK FOR ENHANCING SOURCE LOCATION PRIVACY IN WIRELESS SENSOR NETWORKS "
         

Page(s): 38 - 41
Authors: Keerthi Neeluru

Abstract

Wireless Sensor Networks (WSNs) became popular for many real world applications. The applications include monitoring wildlife habitat, surveillance, studying environments and a host of them in civilian and military context. Especially when WSN is used to have sensitive communications, security is an important concern. The security to messages can be achieved using various existing solutions found in the literature. However, the location of the sensor nodes from which data is collected is also to be secured. Thus source anonymity became a challenge problem in such networks. Unauthorized people can obtain information regarding location of the source of data by analyzing the messages being transferred. Therefore it is inevitable to protect messages and also ensure source anonymity. Recently Amomair et al. presented a framework for analyzing and evaluating source anonymity. This solution uses the notion of "interval indistinguishability" besides using a quantitative measure to achieve desired security in WSN. It also maps the problem to binary hypothesis testing so as to prove the efficiency of the solution. In this paper we implement a solution using NS2 simulations. The empirical results are encouraging.

Keywords— Wireless Sensor Network (WSN), security, source anonymity