车辆网络位置隐私保护方案中的假名变更策略综述

IF 23.8 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Leila Benarous, Sherali Zeadally, Saadi Boudjit, Abdelhamid Mellouk
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引用次数: 0

摘要

由于位置隐私保护直接影响到人身安全,因此在车载网络中位置隐私保护一直是一个需要优先考虑的问题。泄漏和侵犯道路使用者的位置隐私可能是危险的,而不仅仅是好奇,因为它可能扩展到网络跟踪和跟踪。这可能导致道路使用者遭受精神和身体上的痛苦,从勒索到有针对性的广告和陷阱计划。跟踪的结果对道路使用者来说可能是致命的。在过去的17年里,研究人员一直在积极研究车载网络的位置隐私保护机制。许多研究结果已经发表,研究了假名更改策略的使用,这些策略被认为是最合适的解决方案,可以在易于应用,良好的保护级别和网络的正确功能之间保持权衡。我们评估、分类和分析了针对车辆网络位置隐私保护解决方案的假名更改策略,并讨论了它们的性能。我们还回顾了用于评估车辆环境中位置隐私保护解决方案中使用的假名更改技术的模拟工具。本调查的结果将有助于该领域的研究人员在未来开发更强大、高效、经济的位置隐私保护方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review of Pseudonym Change Strategies for Location Privacy Preservation Schemes in Vehicular Networks
Location privacy protection in vehicular networks has been a primary priority to ensure because of its direct impact on human physical safety. Leakage and violation of road users’ location privacy may be perilous beyond simple curiosity as it may scale to cyber-stalking and tracking. This may lead to road users being subjected to mental and physical distress, from blackmailing to targeted advertising, and trap planning. The results of tracking may be fatal to road users. Over the past 17 years, researchers have been actively investigating location privacy protection mechanisms for vehicular networks. Numerous research results have been published that examined the use of pseudonym change strategies which have been considered as the most appropriate solution that maintains the trade-off between ease of application, good protection level and the correct functionality of the network. We evaluate, classify, and analyze pseudonym change strategies aimed at location privacy preserving solutions for vehicular networks and discuss their performance. We also review the simulation tools used for evaluating pseudonym change techniques used in location privacy preserving solutions for the vehicular environment. The results of this survey will help researchers in this field to develop more robust, efficient, and cost-effective location privacy protection schemes in the future.
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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