低能耗的无线传感器网络隐私数据融合方法
Energy-efficient cluster-based privacy data aggregation for wireless sensor networks

针对已有无线传感器网络隐私保护数据融合方法普遍存在节点计算量和通信量较大的问题，基于原有的分簇隐私数据融合方法（CPDA），提出一种低能耗的数据融合隐私保护方法（E-CPDA）。在每轮融合过程中由簇头随机选取协作节点，通过协作节点配合簇头进行数据的隐私保护融合，以有效降低节点的计算量和通信量。仿真结果表明：相比于CPDA方法，E-CPDA方法在保证数据隐私性的前提下，在计算量、通信量和融合精度上都有较大的提升。
Abstract：Current privacy-preserving data aggregation methods in wireless sensor networks often have large computational and communication costs. This paper presents an energy-efficient cluster-based privacy data aggregation (E-CPDA) mechanism based on the cluster-based privacy data aggregation (CPDA) method. In each round of aggregation, the cluster head chooses a node as a collaborative node for the aggregation, which reduces the computational and communication costs between the nodes in one cluster. Simulations show that E-CPDA has less communication and computational costs with good privacy-preserving performance and higher accuracy than CPDA.