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From t-closeness-like privacy to postrandomization via information theory
Rebollo Monedero, David; Forné Muñoz, Jorge; Domingo Ferrer, Josep
Universitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica; Universitat Politècnica de Catalunya. SERTEL - Serveis Telemàtics
t-Closeness is a privacy model recently defined for data anonymization. A data set is said to satisfy t-closeness if, for each group of records sharing a combination of key attributes, the distance between the distribution of a confidential attribute in the group and the distribution of the attribute in the entire data set is no more than a threshold t. Here, we define a privacy measure in terms of information theory, similar to t-closeness. Then, we use the tools of that theory to show that our privacy measure can be achieved by the postrandomization method (PRAM) for masking in the discrete case, and by a form of noise addition in the general case.
Peer Reviewed
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal
Information theory
Informació, Teoria de la
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/publishedVersion
Artículo
         

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