µ -ANT: semantic microaggregation-based anonymization tool

Author:

Sánchez David1,Martínez Sergio1,Domingo-Ferrer Josep1,Soria-Comas Jordi1,Batet Montserrat2

Affiliation:

1. Universitat Rovira i Virgili, UNESCO Chair in Data Privacy, CYBERCAT-Center for Cybersecurity Research of Catalonia, Tarragona, Catalonia E-43007, Spain

2. CYBERCAT-Center for Cybersecurity Research of Catalonia, Internet Interdisciplinary Institute, Universitat Oberta de Catalunya, Castelldefels, Catalonia E-08860, Spain

Abstract

Abstract 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.

Funder

Government of Catalonia

Spanish Government

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Reference12 articles.

1. Discovering hospital admission patterns using models learnt from electronic hospital records;Arandjelovic;Bioinformatics,2015

2. Semantically-grounded construction of centroids for datasets with textual attributes;Martínez;Knowl.-Based Syst,2012

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