Dual-Protection Method Against Eavesdroppers for Distributed State Estimation

This paper examines a security issue for state estimation over a wireless sensor network. The state estimates are transmitted among neighboring nodes through wireless channels in a distributed network, wherein the transmission of the data are vulnerable to the intercept from eavesdroppers, leading to important data privacy leakage. To prevent eavesdroppers from obtaining state estimates, we propose a dual-protection method that combines dynamic transformation with lightweight encryption, which aims to protect the privacy without raising suspicion from eavesdroppers. Furthermore, we consider the scenarios where eavesdroppers utilize side-channel information to gather data and attempt to deduce the encryption mechanism, subsequently inferring the real state estimate. We also provide the analysis to show that the eavesdropper with inference capabilities could not influence the estimation performance of sensors. Finally, the numerical examples are provided to illustrate the effectiveness of the privacy-preserving method.