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Optimized Query Forgery for Private Information Retrieval

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2 Author(s)
Rebollo-Monedero, D. ; Dept. of Telematics Eng., Tech. Univ. of Catalonia (UPC), Barcelona, Spain ; Forne, J.

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.

Published in:

Information Theory, IEEE Transactions on  (Volume:56 ,  Issue: 9 )

Date of Publication:

Sept. 2010

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