Perturbation of Numerical Confidential Data via Skew-t Distributions

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dc.contributor.authorLee, Seokho
dc.contributor.authorGenton, Marc G.
dc.contributor.authorArellano Valle, Reinaldo B.
dc.date.accessioned2024-01-10T12:07:29Z
dc.date.available2024-01-10T12:07:29Z
dc.date.issued2010
dc.description.abstractWe propose a new data perturbation method for numerical database security problems based on skew-t distributions. Unlike the normal distribution, the more general class of skew-t distributions is a flexible parametric multivariate family that can model skewness and heavy tails in the data. Because databases having a normal distribution are seldom encountered in practice, the newly proposed approach, coined the skew-t data perturbation (STDP) method, is of great interest for database managers. We also discuss how to preserve the sample mean vector and sample covariance matrix exactly for any data perturbation method. We investigate the performance of the STDP method by means of a Monte Carlo simulation study and compare it with other existing perturbation methods. Of particular importance is the ability of STDP to reproduce characteristics of the joint tails of the distribution in order for database users to answer higher-level questions. We apply the STDP method to a medical database related to breast cancer.
dc.fechaingreso.objetodigital2024-05-16
dc.format.extent16 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1287/mnsc.1090.1104
dc.identifier.eissn1526-5501
dc.identifier.issn0025-1909
dc.identifier.urihttps://doi.org/10.1287/mnsc.1090.1104
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/76290
dc.identifier.wosidWOS:000274442300007
dc.information.autorucMatemática;Arellano-Valle RB;S/I;58107
dc.issue.numero2
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final333
dc.pagina.inicio318
dc.publisherINFORMS
dc.revistaMANAGEMENT SCIENCE
dc.rightsacceso restringido
dc.subjectconfidentiality
dc.subjectdatabase management
dc.subjectkurtosis
dc.subjectmultivariate
dc.subjectsecurity
dc.subjectsimulation
dc.subjectskewness
dc.subjectSECURITY
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titlePerturbation of Numerical Confidential Data via Skew-t Distributions
dc.typeartículo
dc.volumen56
sipa.codpersvinculados58107
sipa.indexWOS
sipa.indexScopus
sipa.trazabilidadCarga SIPA;09-01-2024
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