基于均衡增量近邻查询的位置隐私保护方法

庄礼金; 欧毓毅; 凌捷

doi:10.11959/j.issn.1000-0801.2016205

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基于均衡增量近邻查询的位置隐私保护方法

研究与开发 | 更新时间：2024-06-05

- 基于均衡增量近邻查询的位置隐私保护方法
- Location privacy protection technology based on KHINN
- 电信科学 2016年32卷第9期页码：89-94
- 作者机构：
- 作者简介：
  
  [ "庄礼金(1990-)，女，广东工业大学计算机学院硕士生，主要研究方向为网络信息安全技术。" ]
  [ "欧毓毅(1974-)，女，博士，广东工业大学计算机学院主任、副教授，主要研究方向为信息系统集成。" ]
  [ "凌捷(1964-)，男，博士，广东工业大学计算机学院院长、教授，主要研究方向为网络信息安全技术、计算机网络通信。" ]
- 基金信息：
  
  广东省科技计划基金资助项目;The Science and Technology Project of Guangdong Province(2015B010128014);广东省重大科技专项基金资助项目;Guangdong Provincial Major Scientific and Technological Special(2015B010108002);广东省科技计划基金资助项目;The Science and Technology Project of Guangdong Province(2015B090906015);广东省教育部产学研合作资助项目;Guangdong Provincial Education Department Research Cooperation Project(2014A010103029);广东省科技计划产学研合作项目;Guangdong Province Science and Technology Plan(2014B090908010);广东省教育部产学研合作资助项目;Guangdong Provincial Education Department Research Cooperation Project(2014B090901053)
- DOI：10.11959/j.issn.1000-0801.2016205
  中图分类号： TP309
- 网络出版日期：2016-09，
  
  纸质出版日期：2016-09-15
- 稿件说明：
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庄礼金, 欧毓毅, 凌捷. 基于均衡增量近邻查询的位置隐私保护方法[J]. 电信科学, 2016,32(9):89-94.

Lijin ZHUANG, Yuyi OU, Jie LING. Location privacy protection technology based on KHINN[J]. Telecommunications science, 2016, 32(9): 89-94.
庄礼金, 欧毓毅, 凌捷. 基于均衡增量近邻查询的位置隐私保护方法[J]. 电信科学, 2016,32(9):89-94. DOI： 10.11959/j.issn.1000-0801.2016205.

Lijin ZHUANG, Yuyi OU, Jie LING. Location privacy protection technology based on KHINN[J]. Telecommunications science, 2016, 32(9): 89-94. DOI： 10.11959/j.issn.1000-0801.2016205.

摘要

针对用户在获得位置服务的同时，用户的位置隐私可能会被泄露的问题，采用协作的分布式模型，移动终端和LBS服务器这两端都使用k-匿名机制，提出基于k-匿名的均衡增量近邻(KHINN)查询方法。该方法在移动终端构造匿名用户组时，利用安全多方求和的技术计算锚点以保证用户隐私；在处理查询结果时，使用基于k-匿名的SpaceTwist方法提高查询隐私度和准确度。经过性能分析和实验结果表明，在考虑用户节点之间半可信或不可信的情况下，可以解决SpaceTwist方法中的查询兴趣点围绕锚点分布不均衡的缺陷问题，提高查询准确度。

Abstract

Aiming at the problem that the user’s location privacy may be leaked while users obtain location-based services

mobile terminal and LBS server the ends use k-anonymity mechanisms using the collaborative distributed model.Balanced incremental nearest neighbor (KHINN)query method based on k-anonymity was proposed.When the method structuring anonymous user group in mobile terminal

secure multiparty summation was used to calculate the anchor point to ensure user privacy;when processing the query results

SpaceTwist method based on k-anonymity was used to improve the query privacy and accuracy.Performance analysis and experimental results show that undering the condition of semi trusted or untrusted users between nodes

the proposed method can solve defects of uneven distribution of discovering points around the anchor point in SpaceTwist method and improve the accuracy of the query.

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references

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