Paper 2024/311 Original: eprint.iacr.org/2024/311 ↗

Aggregating Falcon Signatures with LaBRADOR

Marius A. Aardal
Diego F. Aranha
Katharina Boudgoust
Sebastian Kolby
Akira Takahashi
Abstract

Several prior works have suggested to use non-interactive arguments of knowledge with short proofs to aggregate signatures of Falcon, which is part of the first post-quantum signatures selected for standardization by NIST. Especially LaBRADOR, based on standard structured lattice assumptions and published at CRYPTO’23, seems promising to realize this task. However, no prior work has tackled this idea in a rigorous way. In this paper, we thoroughly prove how to aggregate Falcon signatures using LaBRADOR. We start by providing the first complete knowledge soundness analysis for the non-interactive version of LaBRADOR. Here, the multi-round and recursive nature of LaBRADOR requires a complex and thorough analysis. For this purpose, we introduce the notion of predicate special soundness (PSS). This is a general framework for evaluating the knowledge error of complex Fiat-Shamir arguments of knowledge protocols in a modular fashion, which we believe to be of independent interest. We then explain the exact steps to take in order to adapt the non-interactive LaBRADOR proof system for aggregating Falcon signatures and provide concrete proof size estimates. Additionally, we formalize the folklore approach of obtaining aggregate signatures from the class of hash-then-sign signatures through arguments of knowledge.

Metadata
Available format(s)
PDF
Category
Public-key cryptography
Publication info
Preprint.
History
2024-08-09: last updated
2024-02-23: published
Short URL
https://ia.cr/2024/311
License
https://creativecommons.org/licenses/by/4.0/

BibTeX

@misc{cryptoeprint:2024/311,
      author = {Marius A. Aardal and Diego F. Aranha and Katharina Boudgoust and Sebastian Kolby and Akira Takahashi},
      title = {Aggregating Falcon Signatures with LaBRADOR},
      howpublished = {Cryptology {ePrint} Archive, Paper 2024/311},
      year = {2024},
      url = {https://eprint.iacr.org/2024/311}
}
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