Energy-efficient and privacy-preserving spatial range aggregation query processing in wireless sensor networks

Liang Liu,Zhenhai Hu,Lisong Wang

doi:10.1177/1550147719861005

Abstract

The existing privacy-preserving aggregation query processing methods in sensor networks rely on pre-established network topology and require all nodes in the network to participate in query processing. Maintaining the topology results in a large amount of energy overhead, and in many cases, the user is interested only in the aggregated query results of some areas in the network, and thus, the participation of the entire network node is not necessary. Aiming to solve this problem, this article proposes a spatial range aggregation query algorithm for a dynamic sensor network with privacy protection (energy-efficient privacy-preserving data aggregation). The algorithm does not rely on the pre-established topology but considers only the query area that the user is interested in, abandoning all nodes to participate in distributing the query messages while gathering the sensory data in the query range. To protect node data privacy, Shamir’s secret sharing technology is used to prevent internal attackers from stealing the sensitive data of the surrounding nodes. The analysis and experimental results show that the proposed algorithm outperforms the existing algorithms in terms of energy and privacy protection.

Highlights

A wireless sensor network (WSN) is a multihop selforganizing network composed of multiple sensor nodes
The existing aggregation query privacy protection algorithm, Slice-Mix-AggRegaTe (SMART),[10] and its variants privacy preserving, energy-efficient and scalable continuous data aggregation (PECDA)[11] and adaptive slice-based secure data aggregation (ASSDA),[12] hide original and sensing data by slicing the data. These algorithms have certain privacy protection capabilities, they all assume that the query area is the entire monitoring area, and all nodes in the network are required to participate in query processing
In E2PDA, if an attacker wants to get the original data of a node n, he needs to get the aggregation result sent to the node n and the data transmitted to n’s node after node n completes the aggregation operation

Summary

Introduction

A wireless sensor network (WSN) is a multihop selforganizing network composed of multiple sensor nodes. The existing aggregation query privacy protection algorithm, Slice-Mix-AggRegaTe (SMART),[10] and its variants privacy preserving, energy-efficient and scalable continuous data aggregation (PECDA)[11] and adaptive slice-based secure data aggregation (ASSDA),[12] hide original and sensing data by slicing the data These algorithms have certain privacy protection capabilities, they all assume that the query area is the entire monitoring area, and all nodes in the network are required to participate in query processing. The existing privacy-preserving aggregation query algorithms rely on pre-established topologies, which can be divided into two categories according to their topology type: tree-based algorithms and cluster-based algorithms He et al.[10] proposed data aggregation privacy protection technology, SMART, based on data fragmentation. SMART adopted the random secret key allocation strategy proposed in Eschenauer and Gligor,[39] which is mainly composed of three stages: 1. Secret key pre-allocation: There are K secret keys in the secret key pool, and each sensor node in the sensor network randomly selects k secret keys from the pool

Discovery of shared secret keys

Data aggregation

Summary