Authors:
Sain Saginbekov
1
and
Dossay Oryspayev
2
Affiliations:
1
Computer Science Department, School of Engineering and Digital Sciences, Nazarbayev University, Nur-Sultan 010000, Kazakhstan
;
2
Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, U.S.A.
Keyword(s):
Wireless Sensor Networks, Source Location Privacy, Global Adversary.
Abstract:
Wireless Sensor Networks (WSNs) consist of a number of resource-constrained sensor nodes and a designated node called a sink, which collects data from the sensor nodes. A WSN can be used in numerous applications such as subject tracking and monitoring, where it is often desirable to keep the location of the subject private. In these types of applications, an adversary can locate the monitored subject, if a location privacy protection scheme is not applied. In this paper, we propose an adaptive energy and delay efficient scheme, called Snowflake, that conceals the location of subjects from a global adversary. Snowflake can be adapted to make the delivery delay smaller, or to make the packet overhead low. The simulation results show that Snowflake performs better than an existing algorithm.