Query-Aware Location Privacy Model Based on p-Sensitive and k-Anonymity for Road Networks

Chen, Jiahui; Xu, Hongyun; Lin, Zhu

doi:10.1007/978-3-642-32427-7_22

Cited by 3 publications

(1 citation statement)

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“…K-anonymity means unless there are k-1 data that are released at the same time the k-user can be disclosed. Chen et al [20] propose a query-aware location privacy scheme based on p-sensitive and kanonymity for road networks, which puts all the k users as an anonymous entity in a certain area and authority uses the optimized queries to determine a specific entity. The study of Cabellero-Gil et al [21] is also based on k anonymous algorithm, but it takes into account the tracking after the anonymous abuse.…”

Section: Related Workmentioning

confidence: 99%

A VANET privacy protection scheme based on fair blind signature and secret sharing algorithm

Wang

Zhao

et al. 2017

Automatika

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Vehicular ad hoc network (VANET) is a traffic application of wireless sensor network, which is also a new mobile ad hoc networks composed of vehicle nodes, roadside units, service providers and other components. In VANET, data is transmitted by the wireless channel, which is subject to potential threat like information leak and data attack due to the openness and sensitivity of the auto organization network itself. How to ensure the identity privacy and trusted communication in VANETs is the key issue to be solved urgently. The existing work usually uses authentication mechanism, but the user's privacy disclosure is inevitable during the authentication process. Some anonymous authentication schemes have been proposed to solve the problem of privacy disclosure regardless of considering anonymity abuse. However, anonymity abuse is also severe in VANET. In view of the above problems, this paper proposes a scheme based on fair blind signature and secret sharing algorithm. By security analysis and experiment, the scheme has been proved to be higher anonymity and higher efficiency. KEYWORDSVehicular ad hoc network; anonymous authentication; track; fair blind signature; secret sharing algorithm

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Section: Related Workmentioning

confidence: 99%