Energy-Efficient Privacy Preserving Data Aggregation Protocols Based on Slicing

Abstract

Wireless sensor networks (WSNs) are widely involved in many fields. However, the broadcast communication mode and the unattended nature make sensor nodes be the target of attackers, which leads to the privacy disclosure of network. Slice-Mix-AggRegaTe (SMART) scheme divides the data into pieces and sends the pieces to different nodes in order to hide the sensitive information. However, SMART needs to frequently exchange data among a network, which brings tremendous communication overhead to sensor nodes. Faced with the above mentioned issues, this paper first proposes Energy-efficient Privacy Preserving data Aggregation protocol based on slicing (EPPA). We adopt a new slicing mode to reduce the numbers of slices, which can significantly prevent the data from being compromised and decrease the communication overhead. Meanwhile, an enhanced scheme based on EPPA called the Multi-function Privacy Preserving data Aggregation protocol (MPPA) is presented. MPPA focus on multiple aggregation functions, such as Max/Min, Mean and other aggregation functions. The theoretic analysis and experimental simulation show that the proposed aggregation protocols demonstrate better performance in privacy preserving and communication efficiency than other methods.