Location publishing technology based on differential privacy-preserving for big data services

Lin ZHANG; Yan LIU; Ru-chuan WANG

doi:10.11959/j.issn.1000-436x.2016176

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Location publishing technology based on differential privacy-preserving for big data services

Papers | 更新时间：2024-06-05

- Location publishing technology based on differential privacy-preserving for big data services
- Journal on Communications Vol. 37, Issue 9, Pages: 46-54(2016)
- 作者机构：
  
  1. 南京邮电大学计算机学院，江苏南京 210003
  2. 江苏省无线传感网高技术研究重点实验室，江苏南京 210003
  3. 南京邮电大学宽带无线通信与传感网技术教育部重点实验室，江苏南京 210003
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61402241);The National Natural Science Foundation of China(61572260);The National Natural Science Foundation of China(61373017);The National Natural Science Foundation of China(61572261);The National Natural Science Foundation of China(61472192);Scientific and Technological Support Project of Jiangsu Province(BE2015702);The Natural Science Key Fund for Colleges and Universities of Jiangsu Province(12KJA520002);Natural Science Key Fund for Col-leges and Universities of Jiangsu Province(14KJA520002)
- DOI：10.11959/j.issn.1000-436x.2016176
  CLC： TP393
- Online First：2016-09，
  
  Published：25 September 2016
- 稿件说明：
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Lin ZHANG, Yan LIU, Ru-chuan WANG. Location publishing technology based on differential privacy-preserving for big data services[J]. Journal on Communications, 2016, 37(9): 46-54.
DOI：

Lin ZHANG, Yan LIU, Ru-chuan WANG. Location publishing technology based on differential privacy-preserving for big data services[J]. Journal on Communications, 2016, 37(9): 46-54. DOI： 10.11959/j.issn.1000-436x.2016176.

摘要

应对多组合复杂攻击及前景知识攻击，提出一种新的基于差分隐私保护机制的位置大数据发布模型，创新设计可用性评估反馈机制模块，引入时间变量动态地针对敏感属性以及身份识别等分析模型的服务质量，能在位置大数据与非位置大数据相结合、用户背景知识不确定等情况下保护用户的位置隐私。仿真实验基于多种空间索引技术验证了新发布模型能够在指定的私密性条件下，为位置查询服务发布具有更高准确率的匿名数据。

Abstract

Aiming at dealing with prospect knowledge and complex combinatorial attack

a new location big data publishing mechanism under differential privacy technology was given.And innovative usability evaluation feedback mechanism was designed.It gave corresponding solution details for the sensitive attributes and the identity recognition to analyze the quality of service

aimed at privacy protecting for location based big data under situations like combination of location information and non-location information and attacker’s arbitrary background knowledge.Simulation results based on different spatial indexing technology proved that the new publishing model has a higher accuracy under specified privacy conditions for the location query service.

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references

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