Recent advances in optimization techniques for statistical tabular data protection
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Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/15074
Tipus de documentReport de recerca
Data publicació2011-03
Condicions d'accésAccés obert
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continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
One of the main services of National Statistical Agencies (NSAs) for the current Information
Society is the dissemination of large amounts of tabular data, which is obtained
from microdata by crossing one or more categorical variables. NSAs must guarantee that
no confidential individual information can be obtained from the released tabular data. Several
statistical disclosure control methods are available for this purpose. These methods
result in large linear, mixed integer linear, or quadratic mixed integer linear optimization
problems. This paper reviews some of the existing approaches, with an emphasis on two
of them: cell suppression problem (CSP) and controlled tabular adjustment (CTA). CSP
and CTA have concentrated most of the recent research in the tabular data protection field.
The particular focus of this work is on methods and results of practical interest for end-users
(mostly, NSAs). Therefore, in addition to the resulting optimization models and solution approaches,
computational results comparing the main optimization techniques—both optimal
and heuristic—using real-world instances are also presented.
CitacióCastro, J. "Recent advances in optimization techniques for statistical tabular data protection". 2011.
Forma partDR 2011/03
URL repositori externhttp://www-eio.upc.es/~jcastro/publications/reports/dr2011-03.pdf
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