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dc.contributor.authorNin Guerrero, Jordi
dc.contributor.authorHerranz Sotoca, Javier
dc.contributor.authorTorra i Reventós, Vicenç
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Matemàtica Aplicada IV
dc.date.accessioned2011-07-11T09:33:15Z
dc.date.available2011-07-11T09:33:15Z
dc.date.created2008
dc.date.issued2008
dc.identifier.citationNin, J.; Herranz, J.; Torra, V. Attribute selection in multivariate microaggregation. A: International Workshop on Privacy and Anonymity in Information Society. "2008 International Workshop on Privacy and Anonymity in Information Society". Nantes: 2008, p. 51-60.
dc.identifier.isbn78-1-59593-965-4
dc.identifier.urihttp://hdl.handle.net/2117/12909
dc.description.abstractMicroaggregation is one of the most employed microdata protection methods. The idea is to build clusters of at least k original records, and then replace them with the centroid of the cluster. When the number of attributes of the dataset is large, a common practice is to split the dataset into smaller blocks of attributes. Microaggregation is successively and independently applied to each block. In this way, the effect of the noise introduced by microaggregation is reduced, but at the cost of losing the k-anonymity property. The goal of this work is to show that, besides of the specific microaggregation method employed, the value of the parameter k, and the number of blocks in which the dataset is split, there exists another factor which can influence the quality of the microaggregation: the way in which the attributes are grouped to form the blocks. When correlated attributes are grouped in the same block, the statistical utility of the protected dataset is higher. In contrast, when correlated attributes are dispersed into different blocks, the achieved anonymity is higher, and, so, the disclosure risk is lower. We present quantitative evaluations of such statements based on different experiments on real datasets.
dc.format.extent10 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Informàtica::Seguretat informàtica
dc.subject.lcshData protection
dc.subject.otherAttribute selection
dc.subject.otherMicroaggregation
dc.subject.otherStatistical disclosure control
dc.titleAttribute selection in multivariate microaggregation
dc.typeConference report
dc.subject.lemacProtecció de dades
dc.contributor.groupUniversitat Politècnica de Catalunya. MAK - Matemàtica Aplicada a la Criptografia
dc.identifier.doi10.1145/1379287.1379299
dc.rights.accessRestricted access - publisher's policy
drac.iddocument2631063
dc.description.versionPostprint (published version)
upcommons.citation.authorNin, J.; Herranz, J.; Torra, V.
upcommons.citation.contributorInternational Workshop on Privacy and Anonymity in Information Society
upcommons.citation.pubplaceNantes
upcommons.citation.publishedtrue
upcommons.citation.publicationName2008 International Workshop on Privacy and Anonymity in Information Society
upcommons.citation.startingPage51
upcommons.citation.endingPage60


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