基于均衡增量近邻查询的位置隐私保护方法

doi:10.11959/j.issn.1000-0801.2016205

电信科学 ›› 2016, Vol. 32 ›› Issue (9): 89-94.doi: 10.11959/j.issn.1000-0801.2016205

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

广东工业大学计算机学院，广东广州 510006

出版日期:2016-09-15 发布日期:2016-10-20
基金资助:
广东省重大科技专项基金资助项目;广东省重大科技专项基金资助项目;广东省教育部产学研合作资助项目;广东省教育部产学研合作资助项目;广东省教育部产学研合作资助项目;广东省教育部产学研合作资助项目

Location privacy protection technology based on KHINN

Lijin ZHUANG,Yuyi OU,Jie LING

Computer College,Guangdong Industry University,Guangzhou 510006,China

Online:2016-09-15 Published:2016-10-20
Supported by:
Guangdong Provincial Major Scientific and Technological Special;Guangdong Provincial Major Scientific and Technological Special;Guangdong Provincial Education Department Research Cooperation Project;Guangdong Provincial Education Department Research Cooperation Project;Guangdong Provincial Education Department Research Cooperation Project;Guangdong Provincial Education Department Research Cooperation Project

摘要/Abstract

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。

关键词: LBS服务器, k-匿名, 锚点, 查询兴趣点, 安全多方求和

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.

Key words: LBSserver, k-anonymous, anchor, querypointofinterest, securesum

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.

图/表 5

参考文献 19

[1]	潘晓, 肖珍, 孟小峰 . 位置隐私研究综述[J]. 计算机科学与探索, 2007,1(3): 268-281. PAN X , XIAO Z , MENG X F . Location privacy research review[J]. Journal of Computer Science and Exploration, 2007,1(3): 268-281.
[2]	SWEENEY L . K-anonymity:a model for protecting privacy[J]. International Journal on Uncertainty,Fuzziness and Knowledge-Based Systems, 2002,10(5): 557-570.
[3]	GRUTESER M , GRUNWALD D . Anonymous usage of location-based services through spatial and temporal cloaking[C]// The 1st International Conference on Mobile Systems,Applications and Services,September 11-15,2003,San Francisco,USA. New York:ACM Press, 2003: 31-42.
[4]	GEDIK B , LIU L . Protecting location privacy with personalized k-anonymity:architecture and algorithms[J]. Mobile Computing, 2008,7(1): 1-18.
[5]	GEDIK B , LIU L . A customizable k-anonymity model for protecting location privacy[J]. Icdcs, 2004: 620-629.
[6]	GONG Z , SUN G Z , XIE X . Protecting privacy in location-based services using k-anonymity without cloaked region[C]// Eleventh International Conference on Mobile Data Management,MDM 2010,May 3-6,2010,Kanas City,Missouri,USA. New Jersey:IEEE Press, 2010: 23-26.
[7]	霍峥, 孟小峰, 黄毅 . Private Check In:一种移动社交网络中的轨迹隐私保护方法[J]. 计算机学报, 2013,36(4): 716-726. HUO Z , MENG X F , HUANG Y . Private check in:a method of trajectory of mobile social network privacy protection[J]. Journal of Computers, 2013,36(4): 716-726.
[8]	MOKBEL M F , CHOW C Y , AREF W G . The new casper:query processing for location services without compromising privacy[C]// The International Conference on Very Large Data Bases(VLDB’06),May 12-14,2006,Seoul,South Korea. New York:ACM Press, 2006: 763-774.
[9]	张学军, 桂小林, 伍忠东 . 位置服务隐私保护研究综述[J]. 计算机学报, 2015,26(9): 2373-2395. ZHANG X J , GUI X L , WU Z D . Location privacy protection and research review[J]. Journal of computers, 2015,26(9): 2373-2395.
[10]	KIDO H , YANAGISAWA Y , SATOH T . An anonymous communication technique using dummies for location-based services[C]// International Conference on Pervasive Services,2005 (ICPS’05),July 11-14,2005,Santorini,Greece. New Jersey:IEEE Press, 2005: 88-97.
[11]	YIU M L , JENSEN C S , HUANG X ,et al. Spacetwist:manageing the trade-offs among location privacy,query performance,and query accuracy in mobile services[C]// IEEE 24h International Conference on Data Engineering,April 7-12,2008,Cancun,Mexico. New Jersey:IEEE Press, 2008: 366-375.
[12]	胡德敏, 郑霞 . 基于SpaceTwist的 k-匿名增量近邻查询位置隐私保护算法[J]. 计算机应用研究, 2015(33): 144-162. HU D M , ZHENG X . K-anonymous incremental neighbor query based on SpaceTwist location privacy protection algorithm[J]. Computer Application Research, 2015(33): 144-162.
[13]	周长利, 马春光, 李增鹏 . 一种保护用户隐私的路网兴趣点KNN查询方法[J]. 计算机应用研究, 2016,33(1): 262-265. ZHOU C L , MA C G , LI Z P . A network point of interest to protect the privacy of users KNN query methods[J]. Computer Application Research, 2016,33(1): 262-265.
[14]	黄毅, 霍峥, 孟小峰 . CoPrivacy:一种用户协作无匿名区域的位置隐私保护方法[J]. 计算机学报, 2011,34(10): 1976-1985. HUANG Y , HUO Z , MENG X F . CoPrivacy:a no anonymous user collaboration area of location privacy protection method[J]. Journal of Computers, 2011,34(10): 1976-1985.
[15]	王鹏飞, 李千目, 朱保平 . 基于增量近邻查询的位置隐私保护方法[J]. 计算机科学, 2015,42(3): 158-161. WANG P F , LI Q M , ZHU B P . Location privacy protection method based on incremental neighbor query[J]. Journal of Computer Science, 2015,42(3): 158-161.
[16]	周长利, 马春光, 杨松涛 . 基于敏感位置多样性的 LBS位置隐私保护方法研究[J]. 通信学报, 2015,36(4): 125-136. ZHOU C L , MA C G , YANG S T . LBS location privacy protection method based on position sensitive diversity study[J]. Journal of Communications, 2015,36(4): 125-136.
[17]	LIU X X , LIU K K , GUO L K ,et al. A game-theoretic approach for achieving k-anonymity in location based services[C]// INFOCOM’13,April 14-19,2013,Turin,Italy. New Jersey:IEEE Press, 2013: 2985-2993.
[18]	MIURA K , SATO F . A hybrid method of user privacy protection for location based services[C]// CISIS’13,July 3-5,2013,Taichung,China. New Jersey:IEEE Press, 2008: 55-62.
[19]	BRINKHOFF T . A framework for generating network based moving objects[J]. Geoingormatica, 2000,6(2): 153-180.

方法	可信第三方	匿名成功率	安全性
位置k-匿名方法	有	低	弱
SpaceTwist方法	无	无	弱
HINN方法	无	无	弱
CoPrivacy方法	无	高	较强
本文方法	无	高	强

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

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