Snowflakes: Efficient schemes for source location privacy in Wireless Sensor Networks

A Wireless Sensor Network (WSN) can be used in various applications such as asset monitoring, where the location privacy of the asset is of paramount importance. If such applications do not use a scheme that protects the nodes’ location privacy, an adversary may easily locate the monitored asset. In this paper, we propose two schemes that protect the location privacy of assets from a global adversary. Both schemes are adaptive, energy-efficient, and delay-efficient. The first scheme, called Snowflake, divides the nodes into two types. The first type of nodes transmit packets frequently while the second type of nodes transmit packets less frequently. This approach allows us to improve the performance of the scheme. The second scheme, called Snowflake-S, divides the network area into sectors to reduce the packet overhead further. The simulation results show that our schemes outperform an existing algorithm.