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The limits of differential privacy and its misuse in data release and machine learning

Differential privacy (DP) is a neat privacy definition that can co-exist with certain well-defined data uses in the context of interactive queries. However, DP is neither a silver bullet for all privacy problems nor a replacement for all previous privacy models. In fact, extreme care should be exercised when trying to extend its use beyond the setting it was designed for. This paper reviews the limitations of DP and its misuse for individual data collection, individual data release, and machine learning.

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Additional Info
Field Value
Creator Domingo-Ferrer, Josep josep.domingo@urv.cat
Creator Sánchez, David david.sanchez@urv.cat
Creator Blanco-Justicia, Alberto alberto.blanco@urv.cat
Group Sustainable Cities for Citizens
Publisher arXiv
Source arXiv:2011.02352
Thematic Cluster Privacy Enhancing Technology [PET]
system:type JournalArticle
Management Info
Field Value
Author Wright Joanna
Maintainer Josep Domingo
Version 1
Last Updated 7 September 2023, 18:13 (CEST)
Created 3 February 2021, 14:56 (CET)