Evaluation and protection of multi-level location privacy based on an information theoretic approach

Wenjing ZHANG; Qiao LIU; Hui ZHU

doi:10.11959/j.issn.1000-436x.2019235

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Evaluation and protection of multi-level location privacy based on an information theoretic approach

Papers | 更新时间：2024-06-05

- Evaluation and protection of multi-level location privacy based on an information theoretic approach
- Journal on Communications Vol. 40, Issue 12, Pages: 51-59(2019)
- 作者机构：
  
  西安电子科技大学网络与信息安全学院，陕西西安 710071
- 作者简介：
- 基金信息：
  
  The National Key Research and Development Program of China(2017YFB0802200);The National Natural Science Foundation of China(61932015);The Key Program of the National Natural Science Foundation of China-Guangdong Union Foundation(61672411);The National Natural Science Foundation of China(61902297);The Natural Science Foundation of Shaanxi Province(2019ZDLGY12-02);Shaanxi Innovation Team Project(2018TD-007)
- DOI：10.11959/j.issn.1000-436x.2019235
  CLC： TP393
- Online First：2019-12，
  
  Published：25 December 2019
- 稿件说明：
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Wenjing ZHANG, Qiao LIU, Hui ZHU. Evaluation and protection of multi-level location privacy based on an information theoretic approach[J]. Journal on Communications, 2019, 40(12): 51-59.
DOI：

Wenjing ZHANG, Qiao LIU, Hui ZHU. Evaluation and protection of multi-level location privacy based on an information theoretic approach[J]. Journal on Communications, 2019, 40(12): 51-59. DOI： 10.11959/j.issn.1000-436x.2019235.

摘要

针对位置数据拥有者对数据使用者具有不同的信任程度时，会对使用者进行不同等级的划分并向其发布不同扰动程度的位置数据这一场景中的隐私泄露问题，提出了基于信息论中的互信息的隐私度量方法与保护问题。此外，基于互信息提出了度量攻击者获取不同等级的扰动数据而对真实位置数据进行更精确的推断分析所造成的隐私泄露的方法。借鉴用于求解率失真函数的Blahut-Arimoto算法提出了多等级位置隐私保护机制。实验结果表明，在上述2种问题场景中，所提位置隐私保护机制与基于差分隐私的位置隐私保护方法相比具有更低的隐私泄露，且当真实位置数据具有显著不同的受欢迎程度时，优势更明显。

Abstract

A privacy metric based on mutual information was proposed to measure the privacy leakage occurred when location data owner trust data users at different levels and need to publish the distorted location data to each user according to her trust level

based on which an location privacy protection mechanism (LPPM)was generated to protect user’s location privacy.In addition

based on mutual information

a metric was proposed to measure the privacy leakage caused by attackers obtaining different levels of distorted location data and then performing inference attack on the original location data more accurately.Another privacy metric was also proposed to quantify the information leakage occurred in the scenario based on mutual information.In particular

the proposed privacy mechanism was designed by modifying Blahut-Arimoto algorithm in rate-distortion theory.Experimental results show the superiority of the proposed LPPM over an existing LPPM in terms of location privacyutility tradeoff in both scenarios

which is more conspicuous when there are highly popular locations.

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references

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