Privacy protection in locationbased services: Model and development
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摘要: 近些年来,随着配备定位功能的移动终端数量迅速增加,基于位置服务(LBS)的应用呈现爆炸式的增长,例如查找最邻近的加油站、一公里范围内的所有餐厅等.在用户享受着这些LBS服务为工作、生活带来方便的同时,许多隐私安全问题也逐渐引起了人们的关注.全面了解基于位置服务中现有的隐私保护工作,有利于研究者把握该领域的研究现状、未来发展方向以及存在的挑战.本文对LBS 隐私保护领域中近些年的发展进行了研究总结,重点介绍了LBS隐私保护领域现有的攻击模型、隐私保护模型、度量模型以及数据集,并对现有攻击模型与隐私保护模型进行分类总结,根据其特点进行对比分析,最后探讨了LBS隐私保护目前存在的问题以及未来的发展方向.Abstract: In recent years, with the rapid increase in the number of GPSenabled mobile devices, locationbased services (LBS) applications grow explosively, such as finding the nearest gas station or restaurants within one kilometer and so on. Users benefit from convenience of LBS. However, many privacy issues draw people's attention gradually. Acomprehensive understanding of existing privacy protection work in the locationbased services is important for researchers to grasp the present research status, the future development directionsand the challenges.We give a deep survey of the recent improvement in LBS,which mainly focus on existing attacking models,privacy protection model, measure model and datasets.Whats more, we classifies the existing attacking model and privacy protection model and made comparisons based on different features. Finally unsolved problems and future development are also discussed.
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