Paper 2025/1690 Original: eprint.iacr.org/2025/1690 ↗

A Tight Quantum Algorithm for Multiple Collision Search

Xavier Bonnetain
Johanna Loyer
André Schrottenloher
Yixin Shen
Abstract

Searching for collisions in random functions is a fundamental computational problem, with many applications in symmetric and asymmetric cryptanalysis. When one searches for a single collision, the known quantum algorithms match the query lower bound. This is not the case for the problem of finding multiple collisions, despite its regular appearance as a sub-component in sieving-type algorithms. At EUROCRYPT 2019, Liu and Zhandry gave a query lower bound $\Omega{}(2^{m/3 + 2k/3})$ for finding $2^k$ collisions in a random function with $m$-bit output. At EUROCRYPT 2023, Bonnetain et al. gave a quantum algorithm matching this bound for a large range of $m$ and $k$, but not all admissible values. Like many previous collision-finding algorithms, theirs is based on the MNRS quantum walk framework, but it chains the walks by reusing the state after outputting a collision. In this paper, we give a new algorithm that tackles the remaining non-optimal range, closing the problem. Our algorithm is tight (up to a polynomial factor) in queries, and also in time under a quantum RAM assumption. The idea is to extend the chained walk to a regime in which several collisions are returned at each step, and the "walks" themselves only perform a single diffusion layer.

Metadata
Available format(s)
PDF
Category
Attacks and cryptanalysis
Publication info
Preprint.
History
2025-09-17: last updated
2025-09-17: published
Short URL
https://ia.cr/2025/1690
License
https://creativecommons.org/licenses/by/4.0/

BibTeX

@misc{cryptoeprint:2025/1690,
      author = {Xavier Bonnetain and Johanna Loyer and André Schrottenloher and Yixin Shen},
      title = {A Tight Quantum Algorithm for Multiple Collision Search},
      howpublished = {Cryptology {ePrint} Archive, Paper 2025/1690},
      year = {2025},
      url = {https://eprint.iacr.org/2025/1690}
}
Note: In order to protect the privacy of readers, this archive does not use cookies or embedded third party content.