车联网轨迹隐私保护研究进展

发布时间：2018-01-22 11:25

本文关键词： 车联网轨迹隐私隐私保护　出处：《计算机应用》2017年07期 　论文类型：期刊论文

【摘要】：轨迹隐私保护对车联网(IoV)的发展至关重要,归纳和分析现有研究方法有重要意义。车联网轨迹隐私保护思想有轨迹模糊、假名更换和轨迹加密等3类,实现方法分别有基于用户真实轨迹的方法和基于哑元轨迹的方法、基于混合区域的方法和基于路径混淆的方法、基于私密信息检索(PIR)协议的方法和基于空间转换的方法。首先,介绍和归纳了研究背景和常见攻击等车联网轨迹隐私保护关键问题;然后,从方法思想、科学问题、方法演进等方面详细综述了现有车联网轨迹隐私保护方法,并阐述了需深入研究的难题;在此基础上,总结了代表性方案的隐私保护度、抗攻击性、复杂度等性能指标;最后展望了车联网轨迹隐私保护的未来研究方向。
[Abstract]:Trajectory privacy protection is very important to the development of IoV. It is of great significance to summarize and analyze the existing research methods. There are three kinds of path privacy protection ideas: path ambiguity, pseudonym replacement and trajectory encryption. The implementation methods are based on the real trajectory of the user and the method based on the dummy trace, the method based on the mixed region and the method based on path confusion. The method based on private information retrieval (PIR) protocol and the method based on space conversion. Firstly, the paper introduces and summarizes the research background, common attacks and other key issues of vehicle network trajectory privacy protection. Then, from the aspects of method thought, scientific problem, method evolution and so on, this paper summarizes the existing methods of protecting the privacy of vehicle network track in detail, and expounds the difficult problems that need to be studied deeply. On this basis, the performance index of the representative scheme, such as privacy protection, anti-aggression, complexity and so on, is summarized. Finally, the future research direction of the privacy protection of vehicle network trajectory is prospected.
【作者单位】：同济大学电子与信息工程学院;江苏理工学院计算机工程学院;
【基金】：“十二五”国家科技支撑计划项目(2015BAG13B01) 江苏省前瞻性联合研究项目(BY2014038-03)~~
【分类号】：TN929.5;U495
【正文快照】： 0引言车联网(Internet of Vehicles,Io V)是由车辆自组织网络(Vehicular Ad-Hoc Network,VANET)和移动互联网组成的开放异构网络,支持交通安全、交通效率和信息娱乐等服务[1]。车辆的位置信息是车联网正常运作的基础。通常车辆的位置即是车载用户所在的位置,若不受保护,则用户

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