Location Privacy Attacks on WRSNs

In recent years, although Wireless Rechargeable Sensor Networks (WRSNs) have broken through the energy bottleneck of traditional sensor networks, the wireless charging process has the risk of sensor location privacy leakage, and the attacker can extrapolate the distance by observing the behavior of the mobile charger (MC), leading to a privacy leakage rate as high as 52%, threatening the network topology integrity and data security. In this paper, we construct a hybrid location privacy attack framework, reveal the attack principle, and build the framework based on least squares and center of mass method, and verify its efficiency. After introducing the evaluation method, simulations and experiments show that the model doubles the localization accuracy, but the number of location privacy leaking nodes increases by 33.3%.