International Journal of Recent Trends in Engineering & Research

online ISSN

Source Location Privacy Preservation In Wireless Sensor Networks

Publication Date : 11/02/2016


Author(s) :

Pranil Milind Kale , Gulshan Nimbekar , Nikhil Shankhardhwar , Ashish Palandurkar.


Volume/Issue :
Volume 2
,
Issue 2
(02 - 2016)



Abstract :

Many attackers use the nodes location information for security threats in network, as every sensor node in network is having its own location. An attacker tries to get location information of source or receiver. Wireless sensor networks (WSNs) are group of collection of sensor nodes which are collaboratively communicate with each other for information sharing. The sharing of information is done between source sensor node and sink sensor node using the routing protocols. The major constraint of this network is the security. Thus we need to have source location privacy methods in WSN to prevent such threats from the network. Source privacy preservation is also called source anonymity and recent time this attracts many researchers interests. The attacker or unauthorized sensor node not able to get events location information through the current network traffic is called as source anonymity problem. Recently we have studied efficient method for source anonymity in WSNs. In most of real life applications of WSNs, sensor networks are having the location information about various events and this information needs to secure or anonymous. In that method the statistical framework is presented, this is based on the binary hypothesis testing for modeling, analyzing, and evaluating statistical source anonymity WNS. The concept of notion of interval in distinguish ability in order to model source anonymity, however this method fails to satisfy the notion of interval in distinguish ability practically. Therefore, in this paper we are further extending this method address such issues and practically prove its efficiency, we proposed a modification to existing solutions to improve their anonymity against correlation tests.


No. of Downloads :

7


Indexing