On privacy amplification, lossy compression, and their duality to channel coding
Joseph M. Renes

TL;DR
This paper explores the fundamental connections between privacy amplification, lossy compression, and channel coding, providing new theoretical characterizations and practical protocols that unify these concepts through information-theoretic and coding-theoretic frameworks.
Contribution
It offers a one-shot characterization of privacy amplification rates, links it to channel simulation and lossy compression, and reveals a duality between error-correcting codes and lossy source coding for symmetric channels.
Findings
Finite-blocklength bounds for privacy amplification derived
Protocols for privacy amplification can be adapted for channel simulation
Linear codes for symmetric channels can be transformed into lossy source coding schemes
Abstract
We examine the task of privacy amplification from information-theoretic and coding-theoretic points of view. In the former, we give a one-shot characterization of the optimal rate of privacy amplification against classical adversaries in terms of the optimal type-II error in asymmetric hypothesis testing. This formulation can be easily computed to give finite-blocklength bounds and turns out to be equivalent to smooth min-entropy bounds by Renner and Wolf [Asiacrypt 2005] and Watanabe and Hayashi [ISIT 2013], as well as a bound in terms of the divergence by Yang, Schaefer, and Poor [arXiv:1706.03866 [cs.IT]]. In the latter, we show that protocols for privacy amplification based on linear codes can be easily repurposed for channel simulation. Combined with known relations between channel simulation and lossy source coding, this implies that privacy amplification can be…
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