Open AccessA Statistical Approach to Provide Individualized Privacy for Surveys
Author(s) -
Fernando Esponda,
Kael Huerta,
Vı́ctor M. Guerrero
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0147314
Subject(s) - respondent , computer science , property (philosophy) , sensitivity (control systems) , data science , internet privacy , statistical inference , patient privacy , information sensitivity , data mining , information retrieval , computer security , statistics , mathematics , health care , philosophy , epistemology , electronic engineering , economic growth , political science , law , economics , engineering
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.