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Authors: Joana Ferreira Marques 1 and Jorge Bernardino 2 ; 1

Affiliations: 1 Polytechnic Institute of Coimbra, Coimbra Institute of Engineering, Rua Pedro Nunes, 3030-199 Coimbra, Portugal ; 2 CISUC - Centre of Informatics and Systems of University of Coimbra, Pinhal de Marrocos, 3030-290 Coimbra, Portugal

Keyword(s): GDPR, Personal Data, Anonymization, Pseudonymization, Re-identification, Anonymization Techniques, Suppression, Noise Addition, K-Anonymity, L-Diversity, Re-identification Risks, Anonymization Tools.

Abstract: The privacy of personal data is a very important issue these days. How to process the data and use it for analysis without compromising the individual’s identity is a critical task and must be done in order to ensure the anonymity of this data. To try to unanimously unify this anonymity, laws and regulations such as GDPR were created. In this paper, GDPR will be described and the concepts of anonymization and pseudonymization will be explained. We present some of the main anonymization techniques and efficient software to support the application of these techniques. The main objective is to understand which techniques offer a higher level of anonymization, the strengths and weakness of each one and the advantages in its use.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Marques, J. and Bernardino, J. (2020). Analysis of Data Anonymization Techniques. In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - KEOD; ISBN 978-989-758-474-9; ISSN 2184-3228, SciTePress, pages 235-241. DOI: 10.5220/0010142302350241

@conference{keod20,
author={Joana Ferreira Marques. and Jorge Bernardino.},
title={Analysis of Data Anonymization Techniques},
booktitle={Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - KEOD},
year={2020},
pages={235-241},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010142302350241},
isbn={978-989-758-474-9},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - KEOD
TI - Analysis of Data Anonymization Techniques
SN - 978-989-758-474-9
IS - 2184-3228
AU - Marques, J.
AU - Bernardino, J.
PY - 2020
SP - 235
EP - 241
DO - 10.5220/0010142302350241
PB - SciTePress