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A Statistical Approach to Provide Individualized Privacy for Surveys

In this paper we propose an instrument for collecting sensitive data that allows for each participant to customize the amount of information that she is comfortable revealing. Current methods adopt a uniform approach where all subjects are afforded the same privacy guarantees; however, privacy is a...

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Detalles Bibliográficos
Autores principales: Esponda, Fernando, Huerta, Kael, Guerrero, Victor M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4732602/
https://www.ncbi.nlm.nih.gov/pubmed/26824758
http://dx.doi.org/10.1371/journal.pone.0147314
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author Esponda, Fernando
Huerta, Kael
Guerrero, Victor M.
author_facet Esponda, Fernando
Huerta, Kael
Guerrero, Victor M.
author_sort Esponda, Fernando
collection PubMed
description In this paper we propose an instrument for collecting sensitive data that allows for each participant to customize the amount of information that she is comfortable revealing. Current methods adopt a uniform approach where all subjects are afforded the same privacy guarantees; however, privacy is a highly subjective property with intermediate points between total disclosure and non-disclosure: each respondent has a different criterion regarding the sensitivity of a particular topic. The method we propose empowers respondents in this respect while still allowing for the discovery of interesting findings through the application of well-known inferential procedures.
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spelling pubmed-47326022016-02-04 A Statistical Approach to Provide Individualized Privacy for Surveys Esponda, Fernando Huerta, Kael Guerrero, Victor M. PLoS One Research Article In this paper we propose an instrument for collecting sensitive data that allows for each participant to customize the amount of information that she is comfortable revealing. Current methods adopt a uniform approach where all subjects are afforded the same privacy guarantees; however, privacy is a highly subjective property with intermediate points between total disclosure and non-disclosure: each respondent has a different criterion regarding the sensitivity of a particular topic. The method we propose empowers respondents in this respect while still allowing for the discovery of interesting findings through the application of well-known inferential procedures. Public Library of Science 2016-01-29 /pmc/articles/PMC4732602/ /pubmed/26824758 http://dx.doi.org/10.1371/journal.pone.0147314 Text en © 2016 Esponda et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Esponda, Fernando
Huerta, Kael
Guerrero, Victor M.
A Statistical Approach to Provide Individualized Privacy for Surveys
title A Statistical Approach to Provide Individualized Privacy for Surveys
title_full A Statistical Approach to Provide Individualized Privacy for Surveys
title_fullStr A Statistical Approach to Provide Individualized Privacy for Surveys
title_full_unstemmed A Statistical Approach to Provide Individualized Privacy for Surveys
title_short A Statistical Approach to Provide Individualized Privacy for Surveys
title_sort statistical approach to provide individualized privacy for surveys
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4732602/
https://www.ncbi.nlm.nih.gov/pubmed/26824758
http://dx.doi.org/10.1371/journal.pone.0147314
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