Decoding random linear codes in Õ(20.054n)

  • Authors:
  • Alexander May;Alexander Meurer;Enrico Thomae

  • Affiliations:
  • Faculty of Mathematics, Horst Görtz Institute for IT-Security, Ruhr-University Bochum, Germany;Faculty of Mathematics, Horst Görtz Institute for IT-Security, Ruhr-University Bochum, Germany;Faculty of Mathematics, Horst Görtz Institute for IT-Security, Ruhr-University Bochum, Germany

  • Venue:
  • ASIACRYPT'11 Proceedings of the 17th international conference on The Theory and Application of Cryptology and Information Security
  • Year:
  • 2011

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Abstract

Decoding random linear codes is a fundamental problem in complexity theory and lies at the heart of almost all code-based cryptography. The best attacks on the most prominent code-based cryptosystems such as McEliece directly use decoding algorithms for linear codes. The asymptotically best decoding algorithm for random linear codes of length n was for a long time Stern's variant of information-set decoding running in time $\tilde{\mathcal{O}}\left(2^{0.05563n}\right)$. Recently, Bernstein, Lange and Peters proposed a new technique called Ball-collision decoding which offers a speed-up over Stern's algorithm by improving the running time to $\tilde{\mathcal{O}}\left(2^{0.05558n}\right)$. In this paper, we present a new algorithm for decoding linear codes that is inspired by a representation technique due to Howgrave-Graham and Joux in the context of subset sum algorithms. Our decoding algorithm offers a rigorous complexity analysis for random linear codes and brings the time complexity down to $\tilde{\mathcal{O}}\left(2^{0.05363n}\right)$.