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Treffer: µ -ANT: semantic microaggregation-based anonymization tool.

Title:
µ -ANT: semantic microaggregation-based anonymization tool.
Authors:
Sánchez D; Universitat Rovira i Virgili, UNESCO Chair in Data Privacy, CYBERCAT-Center for Cybersecurity Research of Catalonia, Tarragona, Catalonia E-43007, Spain., Martínez S; Universitat Rovira i Virgili, UNESCO Chair in Data Privacy, CYBERCAT-Center for Cybersecurity Research of Catalonia, Tarragona, Catalonia E-43007, Spain., Domingo-Ferrer J; Universitat Rovira i Virgili, UNESCO Chair in Data Privacy, CYBERCAT-Center for Cybersecurity Research of Catalonia, Tarragona, Catalonia E-43007, Spain., Soria-Comas J; Universitat Rovira i Virgili, UNESCO Chair in Data Privacy, CYBERCAT-Center for Cybersecurity Research of Catalonia, Tarragona, Catalonia E-43007, Spain., Batet M; CYBERCAT-Center for Cybersecurity Research of Catalonia, Internet Interdisciplinary Institute, Universitat Oberta de Catalunya, Castelldefels, Catalonia E-08860, Spain.
Source:
Bioinformatics (Oxford, England) [Bioinformatics] 2020 Mar 01; Vol. 36 (5), pp. 1652-1653.
Publication Type:
Journal Article; Research Support, Non-U.S. Gov't
Language:
English
Journal Info:
Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE
Imprint Name(s):
Original Publication: Oxford : Oxford University Press, c1998-
MeSH Terms:
Biomedical Research* , Data Anonymization*, Humans ; Privacy ; Semantics ; Software
Entry Date(s):
Date Created: 20191018 Date Completed: 20200917 Latest Revision: 20200917
Update Code:
20250114
DOI:
10.1093/bioinformatics/btz792
PMID:
31621826
Database:
MEDLINE

Weitere Informationen

Motivation: Detailed patient data are crucial for medical research. Yet, these healthcare data can only be released for secondary use if they have undergone anonymization.
Results: We present and describe µ-ANT, a practical and easily configurable anonymization tool for (healthcare) data. It implements several state-of-the-art methods to offer robust privacy guarantees and preserve the utility of the anonymized data as much as possible. µ-ANT also supports the heterogenous attribute types commonly found in electronic healthcare records and targets both practitioners and software developers interested in data anonymization.
Availability and Implementation: (source code, documentation, executable, sample datasets and use case examples) https://github.com/CrisesUrv/microaggregation-based_anonymization_tool.
(© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)