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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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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. |
format | Online Article Text |
id | pubmed-4732602 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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