Nature2014-01-07 9:33 PM

Unique in the Crowd: The privacy bounds of human mobility 人群的特定性:人类移动的隐私界限

Abstract We study fifteen months of human mobility data for one and a half million individuals and find that human mobility traces are highly unique. In fact, in a dataset where the location of an individual is specified hourly, and with a spatial resolution equal to that given by the carrier's antennas, four spatio-temporal points are enough to uniquely identify 95% of the individuals. We coarsen the data spatially and temporally to find a formula for the uniqueness of human mobility traces given their resolution and the available outside information. This formula shows that the uniqueness of mobility traces decays approximately as the 1/10 power of their resolution. Hence, even coarse datasets provide little anonymity. These findings represent fundamental constraints to an individual's privacy and have important implications for the design of frameworks and institutions dedicated to protect the privacy of individuals. 论文摘要 我们对150万人群的流动数据进行了15个月的研究发现人群流动的痕迹具有非常大的特定性。事实上,在一个以小时为单位的个人位置数据库,四个时间空间点已经足够用来唯一辨识95%的人口。这些位置数据由个人携带的装备发出。我们在空间和时间上粗化了数据,找到了一个公式来描绘个人特定的流动痕迹。 这一公式显示流动痕迹的唯一性减弱约为它们的分辨率的十分之一 。因此,即使粗化的数据库也提供了一些匿名性。 这个发现说明人类隐私的基本约束,同时它的发现对保护个人隐私的框架和结构的设计具有重要意义。

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