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An Algorithm for k-Anonymous Microaggregation and Clustering Inspired by the Design of Distortion-Optimized Quantizers

Autor
Rebollo-Monedero, D.; Forne, J.; Soriano, M.
Tipus d'activitat
Article en revista
Revista
Data and knowledge engineering
Data de publicació
2011-10-01
Volum
70
Número
10
Pàgina inicial
892
Pàgina final
921
DOI
https://doi.org/10.1016/j.datak.2011.06.005 Obrir en finestra nova
Projecte finançador
CONSEQUENCE
Repositori
http://hdl.handle.net/2117/13052 Obrir en finestra nova
URL
http://www.sciencedirect.com/science/article/pii/S0169023X11000838 Obrir en finestra nova
Resum
We present a multidisciplinary solution to the problems of anonymous microaggregation and clustering, illustrated with two applications, namely privacy protection in databases, and private retrieval of location-based information. Our solution is perturbative, is based on the same privacy criterion used in microdata k-anonymization, and provides anonymity through a substantial modification of the Lloyd algorithm, a celebrated quantization design algorithm, endowed with numerical optimization tech...
Citació
Rebollo-Monedero, D; Forné, J; Soriano, M. An Algorithm for k-Anonymous Microaggregation and Clustering Inspired by the Design of Distortion-Optimized Quantizers. "Data & Knowledge Engineering", 1 Octubre 2001, vol. 70, núm. 10, p. 892-921.
Grup de recerca
ISG - Grup de Seguretat de la Informació
SISCOM - Smart Services for Information Systems and Communication Networks

Participants