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

Author
Castro, J.; Gonzalez, J.
Type of activity
Journal article
Journal
Optimization methods software
Date of publication
2017-06-15
First page
1
Last page
25
DOI
https://doi.org/10.1080/10556788.2017.1332620 Open in new window
Project funding
Very large-scale optimization: methods and applications
Repository
http://hdl.handle.net/2117/108513 Open in new window
http://www-eio.upc.es/~jcastro/publications/reports/dr2017-02.pdf Open in new window
URL
http://www.tandfonline.com/doi/full/10.1080/10556788.2017.1332620 Open in new window
Abstract
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...
Citation
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.
Keywords
benchmarking, data privacy, data science, interior-point methods, lexicographic optimization, linear optimization, statistical disclosure control
Group of research
GNOM - Mathematical Optimization Group

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