华东师范大学学报(自然科学版) ›› 2015, Vol. 2015 ›› Issue (5): 28-45.doi: 10.3969/j.issn.1000-5641.2015.05.003

• 综述论文 • 上一篇    下一篇

LBS的隐私保护:模型与进展

赵大鹏1, 梁磊1, 田秀霞1,2,王晓玲1   

  1. 1. 华东师范大学 数据科学与工程研究院 上海市高可信计算重点实验室,上海200062;
    2.上海电力学院 计算机科学与技术学院,上海201300
  • 收稿日期:2015-09-16 出版日期:2015-09-25 发布日期:2015-10-08
  • 通讯作者: 赵大鹏,男,硕士研究生,研究方向为隐私保护. E-mail:51141500066@ecnu.cn
  • 作者简介:赵大鹏,男,硕士研究生,研究方向为隐私保护.E-mail: 51141500066@ecnu.cn.
  • 基金资助:

    国家自然科学基金(61170085,61472141);上海市重点学科建设项目(B412);上海市可信物联网软件协同创新中心(ZF1213)

Privacy protection in locationbased services: Model and development

ZHAO Da-peng 1,LIANG Lei 1,TIAN Xiu-xia 1,2 ,WANG Xiao-ling1   

  • Received:2015-09-16 Online:2015-09-25 Published:2015-10-08

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.

关键词: 基于位置服务, 隐私保护, 攻击模型, 度量模型, 数据集

Abstract: In recent years, with the rapid increase in the number of GPSenabled mobile devices, locationbased 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 locationbased 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.What′s 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. 

Key words:
locationbased service;privacy protection;attacking model;measure model,
dataset

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