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Authors: Artur Carvalho 1 ; Edna Canedo 2 ; Fernanda Carvalho 3 and Pedro Carvalho 1

Affiliations: 1 Electrical Engineering Department (ENE), University of Brasília (UnB), P.O. Box 4466, Brasília - DF, Brazil ; 2 Electrical Engineering Department (ENE), University of Brasília (UnB), P.O. Box 4466, Brasília - DF, Brazil, Department of Computer Science, University of Brasília (UnB), P.O. Box 4466, Brasília - DF, Brazil ; 3 Law School (FD), University of Brasília (UnB), Brasília - DF, Brazil

Keyword(s): Anonymisation, Big Data, Privacy, Governance, Compliance.

Abstract: Nowadays, in the age of Big Data, we see a growing concern about privacy. Different countries have enacted laws and guidelines to ensure better use of data, especially personal data. Both the General Data Protection Regulation (GDPR) in the EU and the Brazilian General Data Protection Law (LGPD) outline anonymisation techniques as a tool to ensure the safe use of such data. However, the expectations placed on this tool must be reconsidered according to the risks and limits of its use. We discussed whether anonymity used exclusively can meet the demands of Big Data and, at the same time, the demands of privacy and security. We have concluded that, albeit anonymised, the massive use of data must respect good governance practices to preserve personal privacy. In this sense, we point out some guidelines for the use of anonymised data in the context of Big Data.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Carvalho, A.; Canedo, E.; Carvalho, F. and Carvalho, P. (2020). Anonymisation and Compliance to Protection Data: Impacts and Challenges into Big Data. In Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-423-7; ISSN 2184-4992, pages 31-41. DOI: 10.5220/0009411100310041

@conference{iceis20,
author={Artur Carvalho. and Edna Canedo. and Fernanda Carvalho. and Pedro Carvalho.},
title={Anonymisation and Compliance to Protection Data: Impacts and Challenges into Big Data},
booktitle={Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2020},
pages={31-41},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009411100310041},
isbn={978-989-758-423-7},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Anonymisation and Compliance to Protection Data: Impacts and Challenges into Big Data
SN - 978-989-758-423-7
IS - 2184-4992
AU - Carvalho, A.
AU - Canedo, E.
AU - Carvalho, F.
AU - Carvalho, P.
PY - 2020
SP - 31
EP - 41
DO - 10.5220/0009411100310041