Optimized query forgery for private information retrieval

We present a mathematical formulation for the optimization of query forgery for private information retrieval, in the sense that the privacy risk is minimized for a given traffic and processing overhead. The privacy risk is measured as an information- theoretic divergence between the user’s query di...

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Detalles Bibliográficos
Autores: Rebollo Monedero, David|||0000-0002-0783-2382, Forné Muñoz, Jorge|||0000-0002-8401-3292
Tipo de recurso: artículo
Fecha de publicación:2010
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:2117/10267
Acceso en línea:https://hdl.handle.net/2117/10267
https://dx.doi.org/10.1109/TIT.2010.2054471
Access Level:acceso abierto
Palabra clave:Iterative methods (Mathematics)
Entropy
Rate distortion theory
Signal theory (Telecommunication)
Senyal, Teoria del (Telecomunicació)
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació
Descripción
Sumario:We present a mathematical formulation for the optimization of query forgery for private information retrieval, in the sense that the privacy risk is minimized for a given traffic and processing overhead. The privacy risk is measured as an information- theoretic divergence between the user’s query distribution and the population’s, which includes the entropy of the user’s distribution as a special case. We carefully justify and interpret our privacy criterion from diverse perspectives. Our formulation poses a mathematically tractable problem that bears substantial resemblance with rate-distortion theory.