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2016 IEEE 32nd International Conference on Data Engineering (ICDE) (2016)
Helsinki, Finland
May 16, 2016 to May 20, 2016
ISBN: 978-1-5090-2020-1
pp: 1464-1465
Jordi Soria-Comas , UNESCO Chair in Data Privacy, Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain
Josep Domingo-Ferrer , UNESCO Chair in Data Privacy, Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain
David Sanchez , UNESCO Chair in Data Privacy, Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain
Sergio Martinez , UNESCO Chair in Data Privacy, Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain
ABSTRACT
This paper proposes and shows how to use microaggregation to attain t-closeness on top of k-anonymity to protect data releases. The advantages in terms of data utility preservation of microaggregation over classic approaches based on generalizing values are analyzed. Then several microaggregation algorithms for k-anonymous t-closeness are presented and empirically evaluated.
INDEX TERMS
Clustering algorithms, Privacy, Merging, Data privacy, Computational modeling, Partitioning algorithms, Measurement
CITATION

J. Soria-Comas, J. Domingo-Ferrer, D. Sanchez and S. Martinez, "t-closeness through microaggregation: Strict privacy with enhanced utility preservation," 2016 IEEE 32nd International Conference on Data Engineering (ICDE), Helsinki, Finland, 2016, pp. 1464-1465.
doi:10.1109/ICDE.2016.7498376
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