Verifiable Privacy-Preserving Sensor Network Storage for Range Query

For the requirement of low energy consumption and high privacy-preserving in wireless sensor networks of range query, we propose a low energy consumption secure and verifiable range query protocol called SPRQ.SPRQ uses a novel prime aggregation to protect the privacy of the query data; We further propose an idea of the and value chain whereby data items collected by each sensor will be linked with each other just like a chain.The Sink verifies the integrity of query results by checking whether the data chain of each sensor is complete or not. The results of simulation experiments prove that prime aggregation can effectively reduce the amount of increased data in the prefix encoding process,so,network energy consumption is lower compared with other secure range query protocols.

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Using Reduced Paths to Achieve Efficient Privacy-Preserving Range Query in Fog-Based IoT

IEEE Internet of Things Journal ◽

10.1109/jiot.2020.3029472 ◽

2020 ◽

pp. 1-1

Author(s):

Hassan Mahdikhani ◽

Rongxing Lu ◽

Jun Shao ◽

Ali Ghorbani

Keyword(s):

Range Query ◽

Privacy Preserving

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Energy-Efficient Time and Energy Resource Allocation in Non-selfish Symbiotic Cognitive Relaying Sensor Network with Privacy Preserving for Smart City

10.21203/rs.3.rs-52351/v1 ◽

2020 ◽

Author(s):

Ping Li ◽

Yu Liu ◽

Xiang Gao ◽

Huibo Li ◽

Peng Gong

Keyword(s):

Resource Allocation ◽

Energy Efficiency ◽

Sensor Network ◽

Energy Resource ◽

Primary User ◽

Information Privacy ◽

Privacy Preserving ◽

Resource Allocation Algorithm ◽

Allocation Algorithm ◽

Time Resource

Abstract Energy efficiency and privacy preserving have become essential for the wireless sensor networks. In the previous work, an optimal power allocation algorithm was investigated for a non-selfish symbiotic cognitive relaying scheme (NSCRS) in the sensor network with coexistence of a primary user (PU) and cognitive users (CUs). However, the optimal strategy of energy and time resource allocation as well as the privacy preserving was not considered. In this paper, we further consider the joint energy and time resource allocation problem for the cognitive users in NSCRS to maximize the overall capacity of the primary user and cognitive users with the consideration of information privacy under the energy constraints of cognitive users. With full channel state information (CSI), i.e., PU s -PU d , PU s -CUs and CUs-PU d , an optimal energy and time resource allocation algorithm is proposed based on the exhaustive searching. In order to reduce the overhead of CSI feedback, a suboptimal algorithm, in which only the instantaneous CSI of PU s -PU d , the instantaneous CSI of PU s -CUs and an averaged CSI of CUs-PU d by long term observation rather than an instantaneous value of CSI of CUs-PU d are required, is additionally proposed. Simulation results demonstrate the energy efficiency of primary and cognitive users in the NSCRS with consideration of information privacy can be greatly improved by the proposed algorithms.

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Privacy Preserving Data Gathering in Wireless Sensor Network

Network Security, Administration and Management ◽

10.4018/978-1-60960-777-7.ch012 ◽

2011 ◽

pp. 237-251

Author(s):

Md. Golam Kaosar ◽

Xun Yi

Keyword(s):

Wireless Sensor Network ◽

Sensor Network ◽

Perturbation Technique ◽

Data Gathering ◽

Real Life ◽

Privacy Preserving ◽

Wireless Sensor ◽

Individual Data ◽

Data Collection Process ◽

Proposed Model

Sensor devices provide sophisticated services in collecting data in various applications, some of which are privacy sensitive; others are ordinary. This chapter emphasizes the necessity and some mechanisms of privacy preserving data gathering techniques in wireless sensor network communication. It also introduces a new solution for privacy preserving data gathering in wireless sensor networks. By using perturbation technique in a semi-trusted server model, this new solution is capable of reducing a significant amount of computation in data collection process. In this technique, data of a sensor is perturbed into two components which are unified into two semi-trusted servers. Servers are assumed not to collude each other. Neither of them have possession of any individual data. Therefore, they cannot discover individual data. There are many real life applications in which the proposed model can be applied. Moreover, this chapter also shows a technique to collect grouped data from distributed sources keeping the privacy preserved. Security proofs show that any of the servers or any individual sensor neither can discover any individual data nor can associate any data to an individual sensor. Thus, the privacy of individual data is preserved.

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