Research on Time-Serial Location Data Publication Based on Local Differential Privacy

KANG Hai-yan; JI Yuan-rui

doi:10.12263/DZXB.20210338

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Research on Time-Serial Location Data Publication Based on Local Differential Privacy

PAPERS | 更新时间：2025-12-08

- Research on Time-Serial Location Data Publication Based on Local Differential Privacy
- ACTA ELECTRONICA SINICA Vol. 50, Issue 9, Pages: 2222-2232(2022)
- 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：
- 基金信息：
- DOI：10.12263/DZXB.20210338
  CLC： TP309.2
- Received：10 March 2021，
  
  Revised：2021-07-30，
  
  Published：25 September 2022
- 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

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