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arxiv: 1211.5252 · v1 · pith:TWKQCHGFnew · submitted 2012-11-22 · 💻 cs.IT · cs.CR· math.IT

Non-Asymptotic Analysis of Privacy Amplification via Renyi Entropy and Inf-Spectral Entropy

classification 💻 cs.IT cs.CRmath.IT
keywords boundentropyexponentialmin-entropyamplificationbetterblockderived
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This paper investigates the privacy amplification problem, and compares the existing two bounds: the exponential bound derived by one of the authors and the min-entropy bound derived by Renner. It turns out that the exponential bound is better than the min-entropy bound when a security parameter is rather small for a block length, and that the min-entropy bound is better than the exponential bound when a security parameter is rather large for a block length. Furthermore, we present another bound that interpolates the exponential bound and the min-entropy bound by a hybrid use of the Renyi entropy and the inf-spectral entropy.

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