A Novel Location Privacy-Preserving Approach Based on Blockchain

Qiu, Ying; Liu, Yi; Li, Xuan; Chen, Jiahui

doi:10.3390/s20123519

Cited by 38 publications

(34 citation statements)

References 48 publications

(57 reference statements)

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“…They implemented a hybrid approach combining the aforementioned techniques to share geolocation data securely in a trusted execution environment. With a similar aim of targeting the privacy when using location-based services, Qiu et al [54] a location privacy preserving approach that leverages multiple private blockchains to protect the users' privacy without degrading the service's quality. This is still a proofof-concept, but offers a unique service if expanded.…”

Section: ) Security Enhancement Techniquesmentioning

confidence: 99%

A Survey on Privacy-Preserving Blockchain Systems (PPBS) and a Novel PPBS-Based Framework for Smart Agriculture

Tran

Turnbull

et al. 2021

IEEE Open J. Comput. Soc.

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Blockchain and smart contracts have seen significant application over the last decade, revolutionising many industries, including cryptocurrency, finance and banking, and supply chain management. In many cases, however, the transparency provided potentially comes at the cost of privacy. Blockchain does have potential uses to increase privacy-preservation. This paper outlines the current state of privacy preservation utilising Blockchain and Smart Contracts, as applied to a number of fields and problem domains. It provides a background of blockchain, outlines the challenges in blockchain as they relate to privacy, and then classifies into areas in which this paradigm can be applied to increase or protect privacy. These areas are cryptocurrency, data management and storage, e-voting, the Internet of Things, and smart agriculture. This work then proposes PPSAF, a new privacy-preserving framework designed explicitly for the issues that are present in smart agriculture. Finally, this work outlines future directions of research in areas combining future technologies, privacy-preservation and blockchain.

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Section: ) Security Enhancement Techniquesmentioning

confidence: 99%

A Survey on Privacy-Preserving Blockchain Systems (PPBS) and a Novel PPBS-Based Framework for Smart Agriculture

Tran

Turnbull

et al. 2021

IEEE Open J. Comput. Soc.

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“…Based on the vehicle data, the adversary tries to collect two types of information about a vehicle. First, it collects the various location data and tries to match the old location to the vehicle's new location as specified in Equation (40). Secondly, in Equation ( 41), the adversary applies a linking attack to link an old pseudonym with a new pseudonym.…”

Section: R(anonymization) R(anonymization) R(anonymizationmentioning

confidence: 99%

Virtual Pseudonym-Changing and Dynamic Grouping Policy for Privacy Preservation in VANETs

Ullah

Shah

Khan

et al. 2021

Sensors

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Location privacy is a critical problem in the vehicular communication networks. Vehicles broadcast their road status information to other entities in the network through beacon messages to inform other entities in the network. The beacon message content consists of the vehicle ID, speed, direction, position, and other information. An adversary could use vehicle identity and positioning information to determine vehicle driver behavior and identity at different visited location spots. A pseudonym can be used instead of the vehicle ID to help in the vehicle location privacy. These pseudonyms should be changed in appropriate way to produce uncertainty for any adversary attempting to identify a vehicle at different locations. In the existing research literature, pseudonyms are changed during silent mode between neighbors. However, the use of a short silent period and the visibility of pseudonyms of direct neighbors provides a mechanism for an adversary to determine the identity of a target vehicle at specific locations. Moreover, privacy is provided to the driver, only within the RSU range; outside it, there is no privacy protection. In this research, we address the problem of location privacy in a highway scenario, where vehicles are traveling at high speeds with diverse traffic density. We propose a Dynamic Grouping and Virtual Pseudonym-Changing (DGVP) scheme for vehicle location privacy. Dynamic groups are formed based on similar status vehicles and cooperatively change pseudonyms. In the case of low traffic density, we use a virtual pseudonym update process. We formally present the model and specify the scheme through High-Level Petri Nets (HLPN). The simulation results indicate that the proposed method improves the anonymity set size and entropy, provides lower traceability, reduces impact on vehicular network applications, and has lower computation cost compared to existing research work.

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“…Actually, these approaches can always provide privacy preservation to users by using a well-known privacy metric (e.g., k-anonymity [11][12][13][14][15]19] or entropy [1,2,20,21,23]). Moreover, since the emergence of blockchain, some works, such as [27][28][29][30][31][32], combine the LBS and blockchain technology together to protect users' location privacy. The combination is now a new trend and has received more and more attention recently.…”

Section: Introductionmentioning

confidence: 99%

“…To address the privacy issue in LBSs, many approaches have been proposed over the past few years [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 ]. Generally, these approaches can be roughly classified as the: False locations .…”

Section: Introductionmentioning

confidence: 99%

Cache-Based Privacy Preserving Solution for Location and Content Protection in Location-Based Services

Cui

Gao

et al. 2020

Sensors

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Location-Based Services (LBSs) are playing an increasingly important role in people’s daily activities nowadays. While enjoying the convenience provided by LBSs, users may lose privacy since they report their personal information to the untrusted LBS server. Although many approaches have been proposed to preserve users’ privacy, most of them just focus on the user’s location privacy, but do not consider the query privacy. Moreover, many existing approaches rely heavily on a trusted third-party (TTP) server, which may suffer from a single point of failure. To solve the problems above, in this paper we propose a Cache-Based Privacy-Preserving (CBPP) solution for users in LBSs. Different from the previous approaches, the proposed CBPP solution protects location privacy and query privacy simultaneously, while avoiding the problem of TTP server by having users collaborating with each other in a mobile peer-to-peer (P2P) environment. In the CBPP solution, each user keeps a buffer in his mobile device (e.g., smartphone) to record service data and acts as a micro TTP server. When a user needs LBSs, he sends a query to his neighbors first to seek for an answer. The user only contacts the LBS server when he cannot obtain the required service data from his neighbors. In this way, the user reduces the number of queries sent to the LBS server. We argue that the fewer queries are submitted to the LBS server, the less the user’s privacy is exposed. To users who have to send live queries to the LBS server, we employ the l-diversity, a powerful privacy protection definition that can guarantee the user’s privacy against attackers using background knowledge, to further protect their privacy. Evaluation results show that the proposed CBPP solution can effectively protect users’ location and query privacy with a lower communication cost and better quality of service.

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A Novel Location Privacy-Preserving Approach Based on Blockchain

Cited by 38 publications

References 48 publications

A Survey on Privacy-Preserving Blockchain Systems (PPBS) and a Novel PPBS-Based Framework for Smart Agriculture

A Survey on Privacy-Preserving Blockchain Systems (PPBS) and a Novel PPBS-Based Framework for Smart Agriculture

Virtual Pseudonym-Changing and Dynamic Grouping Policy for Privacy Preservation in VANETs

Cache-Based Privacy Preserving Solution for Location and Content Protection in Location-Based Services

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