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

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.

Enhancing Spatial Query Processing Efficiency in IoT Environments Through a Mobile Agent Paradigm

“…Similar to [2], we define valid nodes for a query as nodes residing within the query area and accessible by the Sink. A spatial query processing technique is expected to collect and aggregate data from all valid nodes.…”

“…In many applications, users frequently submit spatial queries to extract and derive information from sensor nodes, obtaining query results over a specific area within a monitored region, all while utilizing the geographic positions of the sensors [1]. In this paper, we are particularly interested in the Windowtype query, as it is one of the most significant spatial query types, retrieving physical data detected from nodes located within a two-dimensional area of interest [2].…”

AEF: Adaptive En-Route Filtering to Extend Network Lifetime in Wireless Sensor Networks

“…References [32,33,34] proposed to improve network lifetime and energy efficiency. The authors of References [35,36,38] focused on energy efficiency and that of References [40,41,42] focused on privacy using various techniques.…”

“…Recent work [20,24,25,26,27] also highlighted countermeasures against attacks in en-route filtering with an emphasis on network lifetime. Several work focused on network lifetime extension [10,28,29,30,31], energy efficiency and network lifetime [32,33,34], and energy efficiency [35,36,37,38,39] and privacy [40,41,42] using various techniques.…”