Privacy- and integrity-preserving range query in wireless sensor networks

Abstract

Abstract-A large-scale wireless sensor network constructed in terms of two-tiered architecture, where cloud nodes take charge of storing sensed data and processing queries with respect to the sensing nodes and querists, incurs security breach. This is because the importance of cloud nodes makes them attractive to adversaries and raises concerns about data privacy and query result correctness. To address these problems, we propose an efficient approach, namely EQ (efficient query), which mainly prevents adversaries from gaining the information processed by or stored in cloud nodes, and detects the compromised cloud nodes when they misbehave. EQ can not only achieve the goals of data privacy and integrity preserving but also ensure the secure range query without incurring false positive. For data privacy preserving, EQ presents an order encryption mechanism by adopting stream cipher to encrypt/decrypt all sensed data such that a cloud node can only process issued queries over stored data in the encryption domain. For data integrity/completeness, we manipulate a data structure of XOR linked list (X2L), which allows a querist to verify the integrity of retrieved data via the socalled verification information, i.e., neighborhood difference in a storage-efficient manner. We demonstrate the feasibility and efficiency of EQ via experiments conducted on TelosB prototype sensor platform running TinyOS 1.1.15 and comparisons with state-of-the-arts.

CSRQ: Communication-Efficient Secure Range Queries in Two-Tiered Sensor Networks

“…The processes of security range queries have been investigated in [ 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 ]. In [ 14 ], Sheng and Li, which is described as S&L below, employed the bucket partition idea to preserve privacy and an authentication encoding mechanism to verify the integrity of query result in two-tiered WSNs.…”

“…The range query refers to accessing all the sensory data items included in a specified range, which can be denoted as a three-tuple: Q t = (ψ, t , [ low , high ]) where ψ denotes the set ID of queried sensor nodes, t is the queried time slot, and low and high refer to the lower and upper bounds of query range, respectively. For example, if Q t = ({ s 1 , s 2 , …, s 8 }, t , [ 10 , 20 ]), it means that Sink finds all data items in [ 10 , 20 ] collected by sensor nodes s 1 – s 8 during a time slot t .…”

“…By using the same threat model in [ 17 , 18 , 19 , 20 , 21 , 22 ], we assume that Sink and the sensor nodes are trusted in two-tiered WSNs, but M is not. In fact, the sensor nodes can also be compromised in a hostile environment.…”

A survey on the privacy-preserving data aggregation in wireless sensor networks

“…In traditional WSNs, private data query represents significant challenges to the design of a resource-constrained WSNs [8][9][10][11][12].…”

VP2RQ: Efficient verifiable privacy-preserving range query processing in two-tiered wireless sensor networks

“…Due to the universal application of range queries among current studies of QP technology for two-tiered WSNs, range QP technology with privacy-preserving and query result completeness verification has attracted a great deal of attention. 11–22 However, current studies show deficiencies in terms of network communication cost, although the communication cost directly impacts the lifetime and application costs of the entire network. The objective of this article is to protect the privacy of sensor data, query results, and the query range and to verify the completeness of query results in two-tiered WSNs; thus, a verifiable privacy-preserving range query (VP 2 RQ) method based on bucket partition is proposed in this article.…”