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On the `Semantics' of Differential Privacy: A Bayesian Formulation. (arXiv:0803.3946v4 [cs.CR] UPDATED)
cs.CR updates on arXiv.org arxiv.org
Differential privacy is a definition of "privacy'" for algorithms that
analyze and publish information about statistical databases. It is often
claimed that differential privacy provides guarantees against adversaries with
arbitrary side information. In this paper, we provide a precise formulation of
these guarantees in terms of the inferences drawn by a Bayesian adversary. We
show that this formulation is satisfied by both "vanilla" differential privacy
as well as a relaxation known as (epsilon,delta)-differential privacy. Our
formulation follows the ideas originally …
adversaries adversary algorithms databases definition differential privacy information privacy terms vanilla