Perspective reformulations of the CTA problem with L_2 distances

Any institution that disseminates data in aggregated form h as the duty to ensure that individual confidential information is not disclosed, either by not releasing data or by perturbing the released data, while maintaining data utility. Controlled tabular adjustment (CTA) is a promising technique o...

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Detalles Bibliográficos
Autores: Castro Pérez, Jordi|||0000-0003-3573-4568, Frangioni, Antonio, Gentile, Claudio
Tipo de recurso: informe técnico
Fecha de publicación:2014
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/26342
Acceso en línea:https://hdl.handle.net/2117/26342
Access Level:acceso abierto
Palabra clave:Mathematical statistics
Mixed Integer Quadratic Programming
Perspective Reformulation
Data Privacy
Statistical Disclosure Control
Tabular Data Protection
Controlled Tabular Adjustment
Classificació AMS::62 Statistics
Classificació AMS::49 Calculus of variations and optimal control
optimization
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Optimització
Descripción
Sumario:Any institution that disseminates data in aggregated form h as the duty to ensure that individual confidential information is not disclosed, either by not releasing data or by perturbing the released data, while maintaining data utility. Controlled tabular adjustment (CTA) is a promising technique of the second type where a protected table that is close to the original one in some chosen distance is constructed. The choice of the specific distance shows a trade-off: while the Euclidean distance has been shown (and is confirmed here) to produce tables with greater “utility”, it gives rise to Mixed Integer Quadratic Problems (MIQPs) with pairs of linked semi-continuous variables that are more difficult to solve than the Mixed Integer Linear Problems corresponding to linear norms. We provide a novel analysis of Perspective Reformulations (PRs) for this special structure; in particular, we devise a Projected PR (P2 R) which is piecewiseconic but simplifies to a (nonseparable) MIQP when the instance is symmetric. We then compare different formulations of the CTA problem, show ing that the ones based on P2 R most often obtain better computational results.