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车联网中基于位置服务的个性化位置隐私保护
引用本文:徐川,丁颖祎,罗丽,刘帅军,刘立祥,赵国锋.车联网中基于位置服务的个性化位置隐私保护[J].软件学报,2022,33(2):699-716.
作者姓名:徐川  丁颖祎  罗丽  刘帅军  刘立祥  赵国锋
作者单位:重庆邮电大学 通信与信息工程学院, 重庆 400065;中国科学院 软件研究所, 北京 100190;中国科学院 软件研究所, 北京 100190;中国科学院大学, 北京 100049
基金项目:国家重点研究发展计划(2018YFB1800301, 2018YFB1800304); 国家自然科学基金(62171070)
摘    要:随着车联网的快速发展,用户享受车联网提供的位置服务(location-based services,LBSs)时,位置隐私泄漏是一个关键安全问题.针对车载网络中位置服务隐私泄露问题,提出了一种基于差分隐私的个性化位置隐私保护方案,在保护用户隐私的前提下,满足用户个性化隐私需求.首先,定义归一化的决策矩阵,描述导航推荐路...

关 键 词:个性化差分隐私  隐私预算分配  最优路径  服务质量
收稿时间:2020/5/27 0:00:00
修稿时间:2020/8/12 0:00:00

Personalized Location Privacy Protection for Location-based Services in Vehicular Networks
XU Chuan,DING Ying-Yi,LUO Li,LIU Shuai-Jun,LIU Li-Xiang,ZHAO Guo-Feng.Personalized Location Privacy Protection for Location-based Services in Vehicular Networks[J].Journal of Software,2022,33(2):699-716.
Authors:XU Chuan  DING Ying-Yi  LUO Li  LIU Shuai-Jun  LIU Li-Xiang  ZHAO Guo-Feng
Affiliation:School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;Institute of Software, Chinese Academy of Sciences, Beijing 100190, China;Institute of Software, Chinese Academy of Sciences, Beijing 100190, China;University of Chinese Academy of Sciences, Beijing 100049, China
Abstract:With the rapid development of vehicular networks, location privacy leakage is a key security issue when users enjoy location- based services (LBSs) provided by vehicular networks. This study proposes a personalized location privacy protection scheme based on differential privacy to address the issue of privacy leakage of location services in vehicular networks, which can meet the personalized privacy needs of users on the premise of protecting their privacy. Firstly, a normalized decision matrix is defined to describe the efficiency and privacy effects of navigation recommendations. Then, the utility model is established by introducing the multi-attribute theory, and the user''s privacy preference is integrated into the model to select the best driving route for the user. Finally, considering the user''s privacy preference, the distance proportion is used as the measurement index to allocate the appropriate privacy budget for the user, and the false location generation range is determined to generate the most effective service request location. Based on the real data set, the proposed scheme is compared with the existing scheme through simulation experiments. The experimental results show that the personalized location privacy protection scheme proposed in this study can meet the service requirements of users and provide higher quality of service (QoS) while reasonably protecting the privacy of them.
Keywords:personalized differential privacy  privacy budget allocation  the optimal route  quality of service (QoS)
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