Towards Practical k-Anonymization: Correlation-based Construction of Generalization Hierarchy

Tomoaki Mimoto, Anirban Basu, Shinsaku Kiyomoto

2016

Abstract

The privacy of individuals included in the datasets must be preserved when sensitive datasets are published. Anonymization algorithms such as k-anonymization have been proposed in order to reduce the risk of individuals in the dataset being identified. k-anonymization is the most common technique of modifying attribute values in a dataset until at least k identical records are generated. There are many algorithms that can be used to achieve k-anonymity. However, existing algorithms have the problem of information loss due to a tradeoff between data quality and anonymity. In this paper, we propose a novel method of constructing a generalization hierarchy for k anonymization algorithms. Our method analyses the correlation between attributes and generates an optimal hierarchy according to the correlation. The effect of the proposed scheme has been verified using the actual data: the average of k of the datasets is 83:14, and it is around 1=3 of the value obtained by conventional methods.

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Paper Citation


in Harvard Style

Mimoto T., Basu A. and Kiyomoto S. (2016). Towards Practical k-Anonymization: Correlation-based Construction of Generalization Hierarchy . In Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 4: SECRYPT, (ICETE 2016) ISBN 978-989-758-196-0, pages 411-418. DOI: 10.5220/0005963804110418


in Bibtex Style

@conference{secrypt16,
author={Tomoaki Mimoto and Anirban Basu and Shinsaku Kiyomoto},
title={Towards Practical k-Anonymization: Correlation-based Construction of Generalization Hierarchy},
booktitle={Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 4: SECRYPT, (ICETE 2016)},
year={2016},
pages={411-418},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005963804110418},
isbn={978-989-758-196-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 4: SECRYPT, (ICETE 2016)
TI - Towards Practical k-Anonymization: Correlation-based Construction of Generalization Hierarchy
SN - 978-989-758-196-0
AU - Mimoto T.
AU - Basu A.
AU - Kiyomoto S.
PY - 2016
SP - 411
EP - 418
DO - 10.5220/0005963804110418