Multi-Dimensional Privacy-Preserving Average Consensus in Wireless Sensor Networks
Longxin Yu, Wenwu Yu, Yuezu Lv · IEEE Transactions on Circuits & Systems II Express Briefs · 2021
This brief studies the privacy preserving average consensus (PPAC) of wireless sensor networks (WSNs). Note that most of the PPAC schemes only focus on the consensus of one-dimensional state, which is not suitable for the actual scenarios. In view of this, the multi-dimensional privacy-preserving average consensus (MPPAC) problem is considered in this brief, where the nodes are divided into two types, the sink nodes and the ordinary ones. A novel MPPAC algorithm is proposed by introducing the super-increasing sequence as well as the RSA algorithm, where the super-increasing sequence plays a key role in tackling the multi-dimensional measurement of the sensors, and the RSA algorithm realizes the privacy preserving average consensus among sink nodes. Simulation results illustrate the effectiveness of this proposed scheme.