Paper 2026/013 Original: eprint.iacr.org/2026/013 ↗

Efficient Threshold ML-DSA

Sofía Celi
Rafaël del Pino
Thomas Espitau
Guilhem Niot
Thomas Prest
Abstract

Threshold signature schemes allow a group of users to jointly generate a digital signature, providing resilience against faults and enhancing decentralization. With the advent of post-quantum cryptography, lattice-based threshold signatures have gained attention as viable PQ-threshold solutions. Nevertheless, existing constructions are limited in terms of their scalability, robustness. Worse, none is compatible with standardized schemes, particularly with the NIST-selected and standardized Module-Lattice-based Digital Signature Algorithm (ML-DSA) algorithm. In this work, we present the first threshold signature scheme that is fully compatible with ML-DSA, supporting secure and efficient signing for a small number of parties, with an average communication per party upper bounded by 1 MB up to 6 parties. Our construction leverages advanced short secret sharing techniques and integrates optimized rejection sampling to achieve a favorable balance between communication efficiency and correctness in distributed environments. We implement our construction in Go and evaluate its performance across local, LAN, and WAN network settings. Our benchmarks demonstrate that our threshold ML-DSA scheme is not only practically deployable but also well-suited for real-world applications, including multi-device cryptocurrency wallets, threshold-based TLS authentication, and for Tor's directory authorities.

Metadata
Available format(s)
PDF
Category
Public-key cryptography
Publication info
Preprint.
History
2026-01-05: last updated
2026-01-05: published
Short URL
https://ia.cr/2026/013
License
https://creativecommons.org/licenses/by/4.0/

BibTeX

@misc{cryptoeprint:2026/013,
      author = {Sofía Celi and Rafaël del Pino and Thomas Espitau and Guilhem Niot and Thomas Prest},
      title = {Efficient Threshold ML-DSA},
      howpublished = {Cryptology {ePrint} Archive, Paper 2026/013},
      year = {2026},
      url = {https://eprint.iacr.org/2026/013}
}
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