A criterion for the measurement of the privacy of user profiles

In previous work, we presented a novel information-theoretic privacy criterion for query forgery in the domain of information retrieval. Our criterion measured privacy risk as a divergence between the users and the populations query distribution, and contemplated the entropy of the users distributio...

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Detalles Bibliográficos
Autores: Rebollo Monedero, David|||0000-0002-0783-2382, Parra Arnau, Javier|||0000-0002-1772-1088, Forné Muñoz, Jorge|||0000-0002-8401-3292
Tipo de recurso: artículo
Fecha de publicación:2013
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:2117/428810
Acceso en línea:https://hdl.handle.net/2117/428810
Access Level:acceso abierto
Palabra clave:Computer networks--Security measures
Ordinadors, Xarxes d'--Mesures de seguretat
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
Descripción
Sumario:In previous work, we presented a novel information-theoretic privacy criterion for query forgery in the domain of information retrieval. Our criterion measured privacy risk as a divergence between the users and the populations query distribution, and contemplated the entropy of the users distribution as a particular case. In this work, we make a twofold contribution. First, we thoroughly interpret and justify the privacy metric proposed in our previous work, elaborating on the intimate connection between the celebrated method of entropy maximization and the use of entropies and divergences as measures of privacy. Secondly, we attempt to bridge the gap between the privacy and the information-theoretic communities by substantially adapting some technicalities of our original work to reach a wider audience, not intimately familiar with information theory and the method of types.