Challenges

• The website with the challenges: decodingchallenge.org.
• Another (older) website with some challenges: wild McEliece.

Documentation

The best algorithms to decode a random code (this problem is called "generic decoding") rely on information set decoding (ISD). The seminal idea is due to Prange (1962) and was imporved independantly by Stern (1988) and Dumer (1991). Since then, new state of the art were proposed to lower the asymptotic exponent. A (non-exhaustive) list of the main papers concerning these algorithms is available in the documentation section of the decoding challenge website. Unfortunately there exists no survey on the state of the art generic decoding algotithms but here is a list of documents that can be useful to understand them.

• Slides of Nicolas Sendreir used in his MOOC "Code-Based Cryptography" (you can watch the videos by registering on the FUN website). The slides are under CC-BY-NC-ND licence.
• Research report by Yann Hamdaoui and Nicolas Sendrier : "A Non Asymptotic Analysis of Information Set Decoding".
• PhD thesis of Alexander Meurer : "A Coding-Theoretic Approach to Cryptanalysis" supervised by Alexander May.
• PhD thesis of Gregory Landais : "Mise en oeuvre de cryptosystèmes basés sur les codes correcteurs d’erreurs et de leurs cryptanalyses" supervised by Nicolas Sendrier.
• PhD thesis of David Hochbach : "Practical Analysis of Information Set Decoding Algorithms" supervised by Alexander Meurer.
• PhD thesis of Anja Becker : "The representation technique: Applications to hard problems in cryptography" supervised by Antoine Joux.
• Slides of the presentation of May, Meurer and Thomae at Asiacrypt 2011.
• Attacking and defending the McEliece cryptosystem article by Bernstein, Lange and Peters, 2008.

Implementations and other existing tools

• Cawof, a software designed by Rodolfo Canto Torres to give the complexity and the optimal parameter choice for the main ISD algorithms.
• ISD algorithm in C implemented by Gregory Landais.
• An implementation of Dumer's algorithm by Valentin Vasseur to solve some challenges.
• The M4RI library for fast arithmetic with dense matrices over F_2 (implementing the method of the four Russians).
• An implementation by Andrea Galimberti found on GitHub (not tested).