Computational privacy : towards privacy-conscientious uses of metadata

Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2015.

Bibliographic Details
Main Author: De Montjoye, Yves-Alexandre
Other Authors: Alex "Sandy" Pentland.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2016
Subjects:
Online Access:http://hdl.handle.net/1721.1/101850
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author De Montjoye, Yves-Alexandre
author2 Alex "Sandy" Pentland.
author_facet Alex "Sandy" Pentland.
De Montjoye, Yves-Alexandre
author_sort De Montjoye, Yves-Alexandre
collection MIT
description Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2015.
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spelling mit-1721.1/1018502022-01-18T16:22:32Z Computational privacy : towards privacy-conscientious uses of metadata Towards privacy-conscientious uses of metadata De Montjoye, Yves-Alexandre Alex "Sandy" Pentland. Massachusetts Institute of Technology. Department of Architecture. Program in Media Arts and Sciences. Program in Media Arts and Sciences (Massachusetts Institute of Technology) Architecture. Program in Media Arts and Sciences. Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2015. Cataloged from PDF version of thesis. Includes bibliographical references (pages 111-127). The breadcrumbs left behind by our technologies have the power to fundamentally transform the health and development of societies. Metadata about our whereabouts, social lives, preferences, and finances can be used for good but can also be abused. In this thesis, I show that the richness of today's datasets have rendered traditional data protections strategies outdated, requiring us to deeply rethink our approach. First, I show that the concept of anonymization, central to legal and technical data protection frameworks, does not scale. I introduce the concept of unicity to study the risks of re-identification of large-scale metadata datasets given p points. I then use unicity to show that four spatio-temporal points are enough to uniquely identify 95% of people in a mobile phone dataset and 90% of people in a credit card dataset. In both cases, I also show that traditional de-identification strategies such as data generalization are not sufficient to approach anonymity in modern high-dimensional datasets. Second, I argue that the second pillar of data protection, risk assessment, is similarly crumbling as data gets richer. I show, for instance, how standard mobile phone data-information on how and when somebody calls or texts-can be used to predict personality traits up to 1.7 times better than random. The risk of inference in big data will render comprehensive risks assessments increasingly difficult and, moving forward, potentially irrelevant as they will require evaluating what can be inferred now, and in the future, from rich data. However, this data has a great potential for good especially in developing countries. While it is highly unlikely that we will ever find a magic bullet or even a one-size- fits-all approach to data protection, there are ways that exist to use metadata in privacy-conscientious ways. I finish this thesis by discussing technical solutions (incl. privacy-through-security ones) which, when combined with legal and regulatory frameworks, provide a reasonable balance between the imperative of using this data and the legitimate concerns of the individual and society. by Yves-Alexandre de Montjoye. Ph. D. 2016-03-25T13:40:22Z 2016-03-25T13:40:22Z 2015 2015 Thesis http://hdl.handle.net/1721.1/101850 942943662 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 127 pages application/pdf Massachusetts Institute of Technology
spellingShingle Architecture. Program in Media Arts and Sciences.
De Montjoye, Yves-Alexandre
Computational privacy : towards privacy-conscientious uses of metadata
title Computational privacy : towards privacy-conscientious uses of metadata
title_full Computational privacy : towards privacy-conscientious uses of metadata
title_fullStr Computational privacy : towards privacy-conscientious uses of metadata
title_full_unstemmed Computational privacy : towards privacy-conscientious uses of metadata
title_short Computational privacy : towards privacy-conscientious uses of metadata
title_sort computational privacy towards privacy conscientious uses of metadata
topic Architecture. Program in Media Arts and Sciences.
url http://hdl.handle.net/1721.1/101850
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