Precision-enhanced and encryption-mixed privacy-preserving data aggregation in wireless sensor networks

Abstract

Security is always a hot topic in wireless sensor networks (WSNs). Privacy-preserving data aggregation has emerged as an important concern in designing data aggregation algorithm. This paper proposes a precision-enhanced and encryption-mixed privacy-preserving data aggregation (PEPDA). The objective is to reduce collision during data transmission and energy consumption and to compensate loss caused by the collision. Based on the Slice-Mix-AggRegaTe (SMART) scheme, it optimizes data slicing by using small data packet, node classifying, and positive and negative data slicing techniques. It also describes a randomized time slot and a data compensation algorithm. Theoretical analysis and simulation show that PEPDA demonstrates a good performance in terms of accuracy, complexity, and security. © 2013 Geng Yang et al.