Eavesdropping Strategies for Remote State Estimation under Communication Constraints.

This paper studies the confidentiality issue of wireless sensor networks under communication constraints from the perspective of an eavesdropper. The considered communication constraints include both medium access constraint and bandwidth limitation. Specifically, the former results in only one sink node gaining access to the shared network at each time step, while the latter requires data to be quantized by a probabilistic quantizer before being transmitted. The task of the eavesdropper is to develop eavesdropping strategies for the constrained network to infer the state of the system as accurately as possible. Since the data is generally unreadable to unauthorized third parties in terms of secure transmission, an eavesdropper with limited power must decide which sink nodes' data needs to be decrypted. By analyzing the impact of different decryption strategies on the eavesdropping performance, a deciphering scheduling is proposed, which minimizes the expected estimation error without exceeding the energy budget. Besides, a recursive reset algorithm is put forward based on the properties of the probabilistic quantizer, which reflects that an eavesdropper can infer whether its own estimate is accurate enough from the decoded data. Moreover, a sufficient condition is established in which the eavesdropping performance is improved under the proposed algorithm. A numerical example is provided to demonstrate the validity of the developed approaches.