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.
CitationRebollo-Monedero, D.; Forné, J. Optimized query forgery for private information retrieval. "IEEE transactions on information theory", Setembre 2010, vol. 56, núm. 9, p. 4631-4642.
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