Precision-Enhanced and Encryption-Mixed Privacy-Preserving Data Aggregation in Wireless Sensor Networks

Abstract EN

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.