Abstract：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.
高志强, 崔翛龙, 杜波, 周沙, 袁琛, 李爱. 满足本地差分隐私的位置数据采集方案[J]. 清华大学学报（自然科学版）, 2019, 59(1): 23-27.
GAO Zhiqiang, CUI Xiaolong, DU Bo, ZHOU Sha, YUAN Chen, LI Ai. Collection scheme of location data based on local differential privacy. Journal of Tsinghua University(Science and Technology), 2019, 59(1): 23-27.
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2019, Vol. 59 
