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A tool for analyzing and fixing infeasible RCTA instances

Autor
Castro, J.; Gonzalez, J.
Tipus d'activitat
Article en revista
Revista
Lecture notes in computer science
Data de publicació
2010-09
Volum
6344
Pàgina inicial
17
Pàgina final
28
DOI
https://doi.org/10.1007/978-3-642-15838-4_2 Obrir en finestra nova
Projecte finançador
MTM2009-08747 Very large-scale optimization for data privacy
Repositori
http://hdl.handle.net/2117/9074 Obrir en finestra nova
URL
http://www.springerlink.com/content/201x3484w0w65611/ Obrir en finestra nova
Resum
Minimum-distance controlled tabular adjustment methods (CTA), and its restricted variants (RCTA), is a recent perturbative approach for tabular data protection. Given a table to be protected, the purpose of RCTA is to find the closest table that guarantees protection levels for the sensitive cells. This is achieved by adding slight adjustments to the remaining cells, possibly excluding a subset of them (usually, the total cells) which preserve their original values. If either protection levels a...
Citació
Castro, J.; González, J. A tool for analyzing and fixing infeasible RCTA instances. "Lecture notes in computer science", Setembre 2010, vol. 6344, p. 17-28.
Paraules clau
Statistical disclosure control Controlled tabular adjustment Mixed integer linear programming Infeasibility in optimization Elastic constraints Elastic filter
Grup de recerca
GNOM - Grup d'Optimització Numèrica i Modelització

Participants