基于本地化差分隐私的时序位置发布方案研究

康海燕; 冀源蕊

doi:10.12263/DZXB.20210338

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基于本地化差分隐私的时序位置发布方案研究

学术论文 | 更新时间：2025-12-08

- 基于本地化差分隐私的时序位置发布方案研究
- Research on Time-Serial Location Data Publication Based on Local Differential Privacy
- 电子学报 2022年50卷第9期页码：2222-2232
- 作者机构：
  
  北京信息科技大学信息管理学院信息安全系，北京 100192
- 作者简介：
  
  [ "康海燕男，1971年7月生，河北石家庄人，博士，教授，北京信息科技大学信息管理学院副院长，研究方向为网络安全与隐私保护等. E-mail: kanghaiyan@126.com" ]
  [ "冀源蕊女，1997年11月生，宁夏银川人，北京信息科技大学网络空间安全专业在读硕士研究生，研究方向为网络安全与隐私保护." ]
- 基金信息：
  
  国家社科基金(21BTQ079);教育部人文社科项目(20YJAZH046);国家自然科学基金(61370139)
- DOI：10.12263/DZXB.20210338
  中图分类号： TP309.2
- 收稿：2021-03-10，
  
  修回：2021-07-30，
  
  纸质出版：2022-09-25
- 稿件说明：
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康海燕,冀源蕊.基于本地化差分隐私的时序位置发布方案研究[J].电子学报,2022,50(09):2222-2232.

KANG Hai-yan,JI Yuan-rui.Research on Time-Serial Location Data Publication Based on Local Differential Privacy[J].ACTA ELECTRONICA SINICA,2022,50(09):2222-2232.
康海燕,冀源蕊.基于本地化差分隐私的时序位置发布方案研究[J].电子学报,2022,50(09):2222-2232. DOI： 10.12263/DZXB.20210338.

KANG Hai-yan,JI Yuan-rui.Research on Time-Serial Location Data Publication Based on Local Differential Privacy[J].ACTA ELECTRONICA SINICA,2022,50(09):2222-2232. DOI： 10.12263/DZXB.20210338.

摘要

为了解决基于位置的服务（Location Based Service， LBS）在收集用户位置数据时造成的隐私泄露，提出一种本地化差分隐私位置发布模型. 首先，该模型采用了灵活的位置隐私保护方案（个性化隐私设置），即由用户选择已设定的多种隐私策略或定制隐私策略，在此基础上设计了定制隐私策略位置扰动算法（Customized Privacy policy Location Perturbation algorithm， CPLP）；其次，提出并设计一种基于隐马尔可夫模型的时序关联位置隐私发布算法（Temporal Relational Location Privacy publishing algorithm，TRLP），解决发布时序位置时产生的隐私泄露；最后，在GeoLife数据集和Gowalla数据集上通过对比实验验证了该模型的有效性.

Abstract

In order to solve the privacy leakage problem in location based service(LBS) when collecting user's location data

we proposed a time-serial location data publication model based on local differential privacy. Firstly

the model adapts a flexible location privacy preservation method

allows users to choose or customize their privacy policy(personalized privacy Settings)

based on customized privacy policy

we designed a customized privacy policy location perturbation algorithm(CPLP); Secondly

we proposed and designed temporal relational location privacy publishing algorithm(TRLP) based on hidden Markov model(HMM)

which can reduce the privacy leakage when releasing the time-serial location data. Finally

we verified the usability of the algorithm on data sets Geolife and Gowalla.

关键词

Keywords

references

BAO J , HE T F , RUAN S J , et al . Planning bike lanes based on sharing-bikes' trajectories [C]// Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining . New York : ACM , 2017 : 1377 - 1386 .

CAO Y , XIAO Y H , TAKAGI S , et al . PGLP: Customizable and rigorous location privacy through policy graph [C]// European Symposium on Research in Computer Security . Cham : Springer , 2020 : 655 - 676 .

GEDIK B , LIU L . Protecting location privacy with personalized k-anonymity: Architecture and algorithms [J]. IEEE Transactions on Mobile Computing , 2008 , 7 ( 1 ): 1 - 18 .

DWORK C , KENTHAPADI K , MCSHERRY F , et al . Our data, ourselves: Privacy via distributed noise generation [C]// Annual International Conference on the Theory and Applications of Cryptographic Techniques . Heidelberg, Berlin : Springer , 2006 : 486 - 503 .

康海燕 , 朱万祥 . 位置服务隐私保护 [J]. 山东大学学报 (理学版) , 2018 , 53 ( 11 ): 35 - 50 .

KANG Hai-yan , ZHU Wan-xiang . Privacy preservation for location-based services [J]. Journal of Shandong University(Natural Science) , 2018 , 53 ( 11 ): 35 - 50 . (in Chinese)

冯登国 , 张敏 , 叶宇桐 . 基于差分隐私模型的位置轨迹发布技术研究 [J]. 电子与信息学报 , 2020 , 42 ( 1 ): 74 - 88 .

FENG D G , ZHANG M , YE Y T . Research on differentially private trajectory data publishing [J]. Journal of Electronics & Information Technology , 2020 , 42 ( 1 ): 74 - 88 . (in Chinese)

郑孝遥 , 罗永龙 , 汪祥舜 , 等 . 基于位置服务的分布式差分隐私推荐方法研究 [J]. 电子学报 , 2021 , 49 ( 1 ): 99 - 110 .

ZHENG X Y , LUO Y L , WANG X S , et al . Research on location-based distributed differential privacy recommendation method [J]. Acta Electronica Sinica , 2021 , 49 ( 1 ): 99 - 110 . (in Chinese)

TAKAGI S , CAO Y , ASANO Y , et al . Geo-graph-indistinguishability: Protecting location privacy for LBS over road networks [C]// IFIP Annual Conference on Data and Applications Security and Privacy . Cham : Springer , 2019 : 143 - 163 .

CORMODE G , PROCOPIUC C , SRIVASTAVA D , et al . Differentially private spatial decompositions [C]// 2012 IEEE 28th International Conference on Data Engineering . Piscataway : IEEE , 2012 : 20 - 31 .

HAY M , LI C , MIKLAU G , et al . Accurate estimation of the degree distribution of private networks [C]// 2009 Ninth IEEE International Conference on Data Mining . Piscataway : IEEE , 2009 : 169 - 178 .

ZHANG J , XIAO X K , XIE X . PrivTree: A differentially private algorithm for hierarchical decompositions [C]// Proceedings of the 2016 International Conference on Management of Data . New York : ACM , 2016 : 155 - 170 .

XIE H R , TANIN E , KULIK L , et al . Euler histogram tree: A spatial data structure for aggregate range queries on vehicle trajectories [C]// Proceedings of the 7th ACM SIGSPATIAL International Workshop on Computational Transportation Science . New York : ACM , 2014 : 18 - 24 .

TO H , NGUYEN K , SHAHABI C . Differentially private publication of location entropy [C]// Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems . New York : ACM , 2016 : 1 - 10 .

CHEN R , FUNG B C M , DESAI B C , et al . Differentially private transit data publication: A case study on the Montreal transportation system [C]// Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining . New York : ACM , 2012 : 213 - 221 .

霍峥 , 孟小峰 . 一种满足差分隐私的轨迹数据发布方法 [J]. 计算机学报 , 2018 , 41 ( 2 ): 400 - 412 .

HUO Z , MENG X F . A trajectory data publication method under differential privacy [J]. Chinese Journal of Computers , 2018 , 41 ( 2 ): 400 - 412 . (in Chinese)

HUA J Y , GAO Y , ZHONG S . Differentially private publication of general time-serial trajectory data [C]// 2015 IEEE Conference on Computer Communications . Piscataway : IEEE , 2015 : 549 - 557 .

ZHAO X D , PI D C , CHEN J F . Novel trajectory privacy-preserving method based on prefix tree using differential privacy [J]. Knowledge-Based Systems , 2020 , 198 : 105940 .

杨高明 , 朱海明 , 方贤进 , 等 . 局部差分隐私约束的关联属性不变后随机响应扰动 [J]. 电子学报 , 2019 , 47 ( 5 ): 1079 - 1085 .

YANG G M , ZHU H M , FANG X J , et al . Invariant post-random response perturbation for correlated attributes under local differential privacy constraint [J]. Acta Electronica Sinica , 2019 , 47 ( 5 ): 1079 - 1085 . (in Chinese)

XIONG S J , SARWATE A D , MANDAYAM N B . Randomized requantization with local differential privacy [C]// 2016 IEEE International Conference on Acoustics, Speech and Signal Processing . Piscataway : IEEE , 2016 : 2189 - 2193 .

SARWATE A D , SANKAR L . A rate-disortion perspective on local differential privacy [C]// 2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton) . Piscataway : IEEE , 2014 : 903 - 908 .

WANG T , ZHANG X F , FENG J Y , et al . A comprehensive survey on local differential privacy toward data statistics and analysis [J]. Sensors (Basel, Switzerland) , 2020 , 20 ( 24 ): 7030 .

GARFINKEL S L , ABOWD J M , POWAZEK S . Issues encountered deploying differential privacy [C]// Proceedings of the 2018 Workshop on Privacy in the Electronic Society . New York : ACM , 2018 : 133 - 137 .

CORMODE G , JHA S , KULKARNI T , et al . Privacy at scale: Local differential privacy in practice [C]// Proceedings of the 2018 International Conference on Management of Data . New York : ACM , 2018 : 1655 - 1658 .

XIAO Y H , XIONG L . Protecting locations with differential privacy under temporal correlations [C]// Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security . New York : ACM , 2015 : 1298 - 1309 .

HARDT M , TALWAR K . On the geometry of differential privacy [C]// Proceedings of the Forty-second ACM Symposium on Theory of Computing . New York : ACM , 2010 : 705 - 714 .

HE X , MACHANAVAJJHALA A , DING B L . Blowfish privacy: Tuning privacy-utility trade-offs using policies [C]// Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data . New York : ACM , 2014 : 1447 - 1458 .

ZHENG Y , XIE X , MA W . GeoLife: A collaborative social networking service among user, location and trajectory .[J]. IEEE Data Eng Bull , 2010 , 33 ( 2 ): 32 - 39 .

CHO E , MYERS S A , LESKOVEC J . Friendship and mobility: User movement in location-based social networks [C]// Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining . New York : ACM , 2011 : 1082 - 1090 .

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