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A linear optimization based method for data privacy in statistical tabular data

Autor
Castro, J.; Gonzalez, J.
Tipus d'activitat
Article en revista
Revista
Optimization methods software
Data de publicació
2017-06-15
Pàgina inicial
1
Pàgina final
25
DOI
https://doi.org/10.1080/10556788.2017.1332620 Obrir en finestra nova
Projecte finançador
Optimización de muy gran escala: métodos y aplicaciones
Repositori
http://hdl.handle.net/2117/108513 Obrir en finestra nova
http://www-eio.upc.es/~jcastro/publications/reports/dr2017-02.pdf Obrir en finestra nova
URL
http://www.tandfonline.com/doi/full/10.1080/10556788.2017.1332620 Obrir en finestra nova
Resum
National Statistical Agencies routinely disseminate large amount of data. Prior to dissemination these data have to be protected to avoid releasing confidential information. Controlled tabular adjustment (CTA) is one of the available methods for this purpose. CTA formulates an optimization problem that looks for the safe table which is closest to the original one. The standard CTA approach results in a mixed integer linear optimization (MILO) problem, which is very challenging for current techno...
Citació
Castro, J., Gonzalez, J. A linear optimization based method for data privacy in statistical tabular data. "Optimization methods software", 15 Juny 2017, p. 1-25.
Paraules clau
benchmarking, data privacy, data science, interior-point methods, lexicographic optimization, linear optimization, statistical disclosure control
Grup de recerca
GNOM - Grup d'Optimització Numèrica i Modelització

Participants

Arxius