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Nibbling MAYO: Optimized Implementations for AVX2 and Cortex-M4

Authors :
Ward Beullens
Fabio Campos
Sofía Celi
Basil Hess
Matthias J. Kannwischer
Source :
Transactions on Cryptographic Hardware and Embedded Systems, Vol 2024, Iss 2 (2024)
Publication Year :
2024
Publisher :
Ruhr-Universität Bochum, 2024.

Abstract

MAYO is a popular high-calorie condiment as well as an auspicious candidate in the ongoing NIST competition for additional post-quantum signature schemes achieving competitive signature and public key sizes. In this work, we present high-speed implementations of MAYO using the AVX2 and Armv7E-M instruction sets targeting recent x86 platforms and the Arm Cortex-M4. Moreover, the main contribution of our work is showing that MAYO can be even faster when switching from a bitsliced representation of keys to a nibble-sliced representation. While the bitsliced representation was primarily motivated by faster arithmetic on microcontrollers, we show that it is not necessary for achieving high performance on Cortex-M4. On Cortex-M4, we instead propose to implement the large matrix multiplications of MAYO using the Method of the Four Russians (M4R), which allows us to achieve better performance than when using the bitsliced approach. This results in up to 21% faster signing. For AVX2, the change in representation allows us to implement the arithmetic much faster using shuffle instructions. Signing takes up to 3.2x fewer cycles and key generation and verification enjoy similar speedups. This shows that MAYO is competitive with lattice-based signature schemes on x86 CPUs, and a factor of 2-6 slower than lattice-based signature schemes on Cortex-M4 (which can still be considered competitive).

Details

Language :
English
ISSN :
25692925
Volume :
2024
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Transactions on Cryptographic Hardware and Embedded Systems
Publication Type :
Academic Journal
Accession number :
edsdoj.33c277bf61a74fc4a5f503520d1aaf31
Document Type :
article
Full Text :
https://doi.org/10.46586/tches.v2024.i2.252-275