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Title:
A trivial debiasing scheme for Helper Data Systems
Authors: Boris Skoric
Abstract:We introduce a debiasing scheme that solves the more-noise-than-entropy problem which can occur in Helper Data Systems when the source is very biased. We perform a condensing step, similar to Index Based Syndrome coding, that reduces the size of the source space in such a way that some source entropy is lost while the noise entropy is greatly reduced. In addition, our method allows for even more entropy extraction by means of a `spamming’ technique. Our method outperforms solutions based on the one-pass and two-pass von Neumann algorithms.
ePrint: https://eprint.iacr.org/2016/241
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