Achieve Location Privacy-Preserving Range Query in Vehicular Sensing

Kong, Qinglei; Lu, Rongxing; Bao, Haiyong

doi:10.3390/s17081829

Cited by 18 publications

(17 citation statements)

References 31 publications

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“…in [18] proposed a range query scheme that can successfully preserve the location privacy of the involved data requesters and vehicles, and protect the confidentiality of the sensed data. Chen et al in [20] proposed a privacy-preserving range query technique.…”

Section: Related Workmentioning

confidence: 99%

Privacy-Aware Fuzzy Range Query Processing Over Distributed Edge Devices

Liu

Zhu

et al. 2022

IEEE Trans. Fuzzy Syst.

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Range query processing is a common edge computing and service in the Internet of Things, which can extract user-interest information from distributed edge devices. How to design lightweight privacy-preserving range query processing methods remains a challenging task. Existing secure range query approaches suffer from both high communication cost and long response time, which makes them unsuitable for edge computing over resource-constrained edge devices. In this paper, we propose two privacy-aware fuzzy query processing schemes based on fuzzy theory. Linguistic range variables, fuzzy overlap information and its recovery mechanism are introduced respectively. In addition, two distributed privacy-aware fuzzy range query processing algorithms are devised. Our approaches not only serve for privacy protection, but also aim to provide other optimal performances in terms of reliability, energy efficiency, and realtime response. Theoretical analysis and experimental evaluations based on real-world data sets validated our motivation.

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Section: Related Workmentioning

confidence: 99%

Privacy-Aware Fuzzy Range Query Processing Over Distributed Edge Devices

Liu

Zhu

et al. 2022

IEEE Trans. Fuzzy Syst.

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“…The experimental results demonstrated the efficiency of the proposed scheme. In 2017, Kong et al [153] designed a secure range query method from distributed on-board storage in VANETs. In this method, the secure computation of scalar products is based on the Paillier algorithm.…”

Section: Data Querymentioning

confidence: 99%

A Survey on Secure Computation Based on Homomorphic Encryption in Vehicular Ad Hoc Networks

Sun

Zhang

et al. 2020

Sensors

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In vehicular ad hoc networks (VANETs), the security and privacy of vehicle data are core issues. In order to analyze vehicle data, they need to be computed. Encryption is a common method to guarantee the security of vehicle data in the process of data dissemination and computation. However, encrypted vehicle data cannot be analyzed easily and flexibly. Because homomorphic encryption supports computations of the ciphertext, it can completely solve this problem. In this paper, we provide a comprehensive survey of secure computation based on homomorphic encryption in VANETs. We first describe the related definitions and the current state of homomorphic encryption. Next, we present the framework, communication domains, wireless access technologies and cyber-security issues of VANETs. Then, we describe the state of the art of secure basic operations, data aggregation, data query and other data computation in VANETs. Finally, several challenges and open issues are discussed for future research.

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“…The network model in this paper is a typical planar periodic data collection wireless sensor network similar to [ 27 , 55 , 56 , 57 ]. Its system model is as follows: There are n homogeneous sensor nodes which are randomly deployed in a two-dimensional planar network with a radius of

, a sink is at the center and the node density is

.…”

Section: System Model and Problem Statementmentioning

confidence: 99%

“…Its system model is as follows: There are n homogeneous sensor nodes which are randomly deployed in a two-dimensional planar network with a radius of

, a sink is at the center and the node density is

. The node communication radius is

[ 2 , 56 ]. The size of a data packet and notification are set to

bytes and

bytes respectively.…”

Section: System Model and Problem Statementmentioning

confidence: 99%

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A Trust-Based Secure Routing Scheme Using the Traceback Approach for Energy-Harvesting Wireless Sensor Networks

Tang

Liu

Zhang

et al. 2018

Sensors

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The Internet of things (IoT) is composed of billions of sensing devices that are subject to threats stemming from increasing reliance on communications technologies. A Trust-Based Secure Routing (TBSR) scheme using the traceback approach is proposed to improve the security of data routing and maximize the use of available energy in Energy-Harvesting Wireless Sensor Networks (EHWSNs). The main contributions of a TBSR are (a) the source nodes send data and notification to sinks through disjoint paths, separately; in such a mechanism, the data and notification can be verified independently to ensure their security. (b) Furthermore, the data and notification adopt a dynamic probability of marking and logging approach during the routing. Therefore, when attacked, the network will adopt the traceback approach to locate and clear malicious nodes to ensure security. The probability of marking is determined based on the level of battery remaining; when nodes harvest more energy, the probability of marking is higher, which can improve network security. Because if the probability of marking is higher, the number of marked nodes on the data packet routing path will be more, and the sink will be more likely to trace back the data packet routing path and find malicious nodes according to this notification. When data packets are routed again, they tend to bypass these malicious nodes, which make the success rate of routing higher and lead to improved network security. When the battery level is low, the probability of marking will be decreased, which is able to save energy. For logging, when the battery level is high, the network adopts a larger probability of marking and smaller probability of logging to transmit notification to the sink, which can reserve enough storage space to meet the storage demand for the period of the battery on low level; when the battery level is low, increasing the probability of logging can reduce energy consumption. After the level of battery remaining is high enough, nodes then send the notification which was logged before to the sink. Compared with past solutions, our results indicate that the performance of the TBSR scheme has been improved comprehensively; it can effectively increase the quantity of notification received by the sink by 20%, increase energy efficiency by 11%, reduce the maximum storage capacity needed by nodes by 33.3% and improve the success rate of routing by approximately 16.30%.

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Achieve Location Privacy-Preserving Range Query in Vehicular Sensing

Cited by 18 publications

References 31 publications

Privacy-Aware Fuzzy Range Query Processing Over Distributed Edge Devices

Privacy-Aware Fuzzy Range Query Processing Over Distributed Edge Devices

A Survey on Secure Computation Based on Homomorphic Encryption in Vehicular Ad Hoc Networks

A Trust-Based Secure Routing Scheme Using the Traceback Approach for Energy-Harvesting Wireless Sensor Networks

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