Mon, 11 Mar 2024 13:00 A New Sieving-Style Information-Set Decoding Algorithm by Vu Nguyen (Lund University)

The problem of decoding random codes is a fundamental problem for code-based cryptography, including recent code-based candidates in the NIST post-quantum standardization process. In this paper, we present a novel sieving-style information-set decoding (ISD) algorithm, addressing the task of solving the syndrome decoding problem. Our approach involves maintaining a list of weight-$2p$ solution vectors to a partial syndrome decoding problem and then creating new vectors by identifying pairs of vectors that collide in $p$ positions. By gradually increasing the parity-check condition by one and repeating this process iteratively, we find the final solution(s). We show that our novel algorithm performs better than other ISDs in the memory-restricted scenario when applied to McEliece. Notably, in the case of problem instances with very low relative weight, it seems to significantly outperform all previous algorithms. In particular, for code-based candidate BIKE, the algorithm has lower bit complexity than the previous best results.

Speaker Bio:

I am Ph.D. student at Lund University. My main research interest is code-based post-quantum cryptography. I also performed cryptanalysis on a few LPN-based post-quantum schemes (wPRF, Firekite).

Venue: Online