Collection scheme of location data based on local differential privacy

被引：0

作者：

Gao Z. ^{[1
]}

Cui X. ^{[1
]}

Du B. ^{[1
]}

Zhou S. ^{[1
]}

Yuan C. ^{[1
]}

Li A. ^{[1
]}

机构：

[1] Urumqi Campus, Engineering University of PAP, Urumqi

来源：

Qinghua Daxue Xuebao/Journal of Tsinghua University | 2019年 / 59卷 / 01期

关键词：

Data collection; Local differential privacy; Location privacy; Randomized response; Statistical learning;

D O I：

10.16511/j.cnki.qhdxxb.2018.22.058

中图分类号：

学科分类号：

摘要：

Methods are needed to protect a person's privacy while monitoring their location. This paper presents a scheme for collecting location data based on local differential privacy. First, a multi-phase randomized response is used to collect the location data based on their local differential privacy. Then, the density of a certain section is estimated using the statistical method and expectation maximization (EM) to analyze the location data. The scheme guarantees that an untrustworthy data collector can still obtain the location statistics without direct access to the original data. Extensive tests verify that EM provides better privacy protection and better utility than the statistical method with limited location data. The results of the statistical method and EM are similar with abundant location data. © 2019, Tsinghua University Press. All right reserved.

引用

页码：23 / 27

页数：4

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