Some cryptanalytic and coding-theoretic applications of a soft stern algorithm - Guo, Qian; Johansson, Thomas; Mårtensson, Erik; Wagner, Paul Stankovski (Advances in mathematics of communications, 2019)
Using the class of information set decoding algorithms is the best known way of decoding general codes, i.e. codes that admit no special structure, in the Hamming metric. The Stern algorithm is the origin of the most efficient algorithms in this class. We consider the same decoding problem but for a channel with soft information. We give a version of the Stern algorithm for a channel with soft information that includes some novel steps of ordering vectors in lists, based on reliability values. We demonstrate how the algorithm constitutes an improvement in some cryptographic and coding theoretic applications. We also indicate how to extend the algorithm to include multiple iterations and soft output values.