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Statistical Decoding

Abstract : The security of code-based cryptography relies primarily on the hardness of generic decoding with linear codes. The best generic decoding algorithms are all improvements of an old algorithm due to Prange: they are known under the name of information set decoding techniques (ISD). A while ago a generic decoding algorithm which does not belong to this family was proposed: statistical decoding. It is a randomized algorithm that requires the computation of a large set of parity-check equations of moderate weight. We solve here several open problems related to this decoding algorithm. We give in particular the asymptotic complexity of this algorithm, give a rather efficient way of computing the parity-check equations needed for it inspired by ISD techniques and give a lower bound on its complexity showing that when it comes to decoding on the Gilbert-Varshamov bound it can never be better than Prange's algorithm.
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https://hal.inria.fr/hal-01661749
Contributor : Thomas Debris-Alazard <>
Submitted on : Tuesday, December 12, 2017 - 1:24:52 PM
Last modification on : Thursday, April 26, 2018 - 10:27:44 AM

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Thomas Debris-Alazard, Jean-Pierre Tillich. Statistical Decoding. ISIT 2017 - IEEE International Symposium on Information Theory, Jun 2017, Aachen, Germany. pp.1789--1802, ⟨10.1109/ISIT.2017.8006839⟩. ⟨hal-01661749⟩

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