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Classical and Quantum Algorithms for Generic Syndrome Decoding Problems and Applications to the Lee Metric

Authors: Chailloux, André; Debris-Alazard, Thomas; Etinski, Simona;

Classical and Quantum Algorithms for Generic Syndrome Decoding Problems and Applications to the Lee Metric

Abstract

The security of code-based cryptography usually relies on the hardness of the syndrome decoding (SD) problem for the Hamming weight. The best generic algorithms are all improvements of an old algorithm by Prange, and they are known under the name of Information Set Decoding (ISD) algorithms. This work aims to extend ISD algorithms' scope by changing the underlying weight function and alphabet size of SD. More precisely, we show how to use Wagner's algorithm in the ISD framework to solve SD for a wide range of weight functions. We also calculate the asymptotic complexities of ISD algorithms both in the classical and quantum case. We then apply our results to the Lee metric, which currently receives a significant amount of attention. By providing the parameters of SD for which decoding in the Lee weight seems to be the hardest, our study could have several applications for designing code-based cryptosystems and their security analysis, especially against quantum adversaries.

Keywords

FOS: Computer and information sciences, Computer Science - Cryptography and Security, Cryptography and Security (cs.CR), [INFO.INFO-CR] Computer Science [cs]/Cryptography and Security [cs.CR]

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Average
Top 10%
Green