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Incremental k-Anonymous microaggregation in large-scale electronic surveys with optimized scheduling

Autor
Rebollo-Monedero, D.; Forne, J.; Soriano, M.
Tipus d'activitat
Article en revista
Revista
IEEE access
Data de publicació
2018-10-15
Volum
6
Pàgina inicial
60016
Pàgina final
60044
DOI
https://doi.org/10.1109/ACCESS.2018.2875949 Obrir en finestra nova
Projecte finançador
Análisis forense avanzado
INcident monitoRing In Smart COmmunities (INRISCO). QoS and Privacy. National Spanish project TEC2014-54335-C4-1-R
Microagregación Anónima en Encuestas Demográficas a Gran Escala
Repositori
http://hdl.handle.net/2117/123435 Obrir en finestra nova
URL
https://ieeexplore.ieee.org/document/8491270 Obrir en finestra nova
Resum
Improvements in technology have led to enormous volumes of detailed personal information made available for any number of statistical studies. This has stimulated the need for anonymization techniques striving to attain a difficult compromise between the usefulness of the data and the protection of our privacy. k-Anonymous microaggregation permits releasing a dataset where each person remains indistinguishable from other k–1 individuals, through the aggregation of demographic attributes, other...
Paraules clau
Data privacy, Electronic surveys, K-anonymity, Large-scale datasets, Microaggregation, Statistical disclosure control
Grup de recerca
ISG - Grup de Seguretat de la Informació
SISCOM - Smart Services for Information Systems and Communication Networks

Participants