Estimating the success of re-identifications in incomplete datasets using generative models

Anonymization has been the main means of addressing privacy concerns in sharing medical and socio-demographic data. Here, the authors estimate the likelihood that a specific person can be re-identified in heavily incomplete datasets, casting doubt on the adequacy of current anonymization practices.

Bibliographic Details
Main Authors: Luc Rocher, Julien M. Hendrickx, Yves-Alexandre de Montjoye
Format: Article
Language:English
Published: Nature Portfolio 2019-07-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-019-10933-3
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author Luc Rocher
Julien M. Hendrickx
Yves-Alexandre de Montjoye
author_facet Luc Rocher
Julien M. Hendrickx
Yves-Alexandre de Montjoye
author_sort Luc Rocher
collection DOAJ
description Anonymization has been the main means of addressing privacy concerns in sharing medical and socio-demographic data. Here, the authors estimate the likelihood that a specific person can be re-identified in heavily incomplete datasets, casting doubt on the adequacy of current anonymization practices.
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spelling doaj.art-6c3c954c3a094ccd81b80c42685232b02022-12-21T19:27:17ZengNature PortfolioNature Communications2041-17232019-07-011011910.1038/s41467-019-10933-3Estimating the success of re-identifications in incomplete datasets using generative modelsLuc Rocher0Julien M. Hendrickx1Yves-Alexandre de Montjoye2Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM), Université catholique de LouvainInformation and Communication Technologies, Electronics and Applied Mathematics (ICTEAM), Université catholique de LouvainDepartment of Computing, Imperial College LondonAnonymization has been the main means of addressing privacy concerns in sharing medical and socio-demographic data. Here, the authors estimate the likelihood that a specific person can be re-identified in heavily incomplete datasets, casting doubt on the adequacy of current anonymization practices.https://doi.org/10.1038/s41467-019-10933-3
spellingShingle Luc Rocher
Julien M. Hendrickx
Yves-Alexandre de Montjoye
Estimating the success of re-identifications in incomplete datasets using generative models
Nature Communications
title Estimating the success of re-identifications in incomplete datasets using generative models
title_full Estimating the success of re-identifications in incomplete datasets using generative models
title_fullStr Estimating the success of re-identifications in incomplete datasets using generative models
title_full_unstemmed Estimating the success of re-identifications in incomplete datasets using generative models
title_short Estimating the success of re-identifications in incomplete datasets using generative models
title_sort estimating the success of re identifications in incomplete datasets using generative models
url https://doi.org/10.1038/s41467-019-10933-3
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