Privacy and Mobile Devices

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  • #177519

    Henry Brown

    A study/paper from

    Title: Unique in the Crowd: The privacy bounds of human mobility

    Authors: Yves-Alexandre de Montjoye, Cesar A. Hidalgo, Michel Verleysen & Vincent D. Blondel

    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.

    Derived from the Latin Privatus, meaning ‘‘withdraw from public life,’’ the notion of privacy has been foundational to the development of our diverse societies, forming the basis for individuals’ rights such as free speech and religious freedom Despite its importance, privacy has mainly relied on informal pro- tection mechanisms. For instance, tracking individuals’ movements has been historically difficult, making them de-facto private. For centuries, information technologies have challenged these informal protection mechanisms. In 1086, William I of England commissioned the creation of the Doomsday book, a written record of major property holdings in England containing individual information collected for tax and draft purposes In the late 19th century, de-facto privacy was similarly threatened by photographs and yellow journalism. This resulted in one of the first publications advocating privacy in the U.S. in which Samuel Warren and Louis Brandeis argued that privacy law must evolve in response to technological changes

    Modern information technologies such as the Internet and mobile phones, however, magnify theuniqueness of individuals, further enhancing the traditional challenges to privacy. Mobility data is among the most sensitive data currently being collected. Mobility data contains the approximate whereabouts of individuals and can be used to reconstruct individuals’ movements across space and time. Individual mobility traces [Fig. 1A–B] have been used in the past for research purposes and to provide personalized services to users . A list of potentially sensitive professional and personal information that could be inferred about an individual knowing only his mobility trace was published recently by the Electronic Frontier Foundation 20. These include the movements of a competitor sales force, attendance of a particular church or an individual’s presence in a motel or at an abortion clinic.

    While in the past, mobility traces were only available to mobile phone carriers, the advent of smartphones and other means of data collection has made these broadly available. For example, Apple recently updated its privacy policy to allow sharing the spatio-temporal location of their users with ‘‘partners and licensees’’ 21 . 65.5B geo-tagged payments are made per year in the US 22 while Skyhook wireless is resolving 400 M user’s WiFi location every day 23 . Furthermore, it is estimated that a third of the 25B copies of applications available on Apple’s App Store SM access a user’s geographic location 24,25 , and that the geo-location of , 50% of all iOS and Android traffic is available to ad networks 26 . All these are fuelling the ubiquity of simply anonymized mobility datasets and are giving room to privacy concern



  • #177522

    Henry Brown

    More information and COMMENTARY from

    Why the collision of big data and privacy will require a new realpolitik
    By David Meyer

    People’s movements are highly predictable, researchers say, making it easy to identify most individuals from supposedly anonymized location datasets. As these datasets have valid uses, this is yet another reason why we need better regulation.

    More information and SOME commentary from BBC:
    Scientists say it is remarkably easy to identify a mobile phone user from just a few pieces of location information.

    Whenever a phone is switched on, its connection to the network means its position and movement can be plotted.

    This data is given anonymously to third parties, both to drive services for the user and to target advertisements.

    But a study in Scientific Reports warns that human mobility patterns are so predictable it is possible to identify a user from only four data points.

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