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2016

A trivial debiasing scheme for Helper Data Systems

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A trivial debiasing scheme for Helper Data Systems
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 von Neumann algorithm.
Boris Skoric
Added 03 Apr 2016
Updated 03 Apr 2016
Type Journal
Year 2016
Where IACR
Authors Boris Skoric
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