Generation of Fast Finite Field Arithmetic forCortex-M4 with ECDH and SQIsign Applications

Finite field arithmetic is central to several cryptographic algorithms on embedded devices like the ARM Cortex-M4, particularly for elliptic curve and isogenybased cryptography. However, rapid algorithm evolution, driven by initiatives such as NIST’s post-quantum standardization, might frequently render hand-optimized implementations obsolete. We address this challenge with m4-modarith, a library generating C code with inline assembly for the Cortex-M4 that rivals custom-tuned assembly, enabling agile development in this ever-changing landscape. Our generated modular multiplications obtains fast performances, competitive with hand-optimized assembly implementations published in the literature, even outperforming some of them for Curve25519. Two contributions are pivotal to this success. First, we introduce a novel multiplication strategy that matches the memory access complexity of the operand caching method while being applicable to a larger cache size for Cortex-M4 implementations. Second, we generalize an efficient pseudo-Mersenne reduction strategy, and formally prove its correctness and applicability for most primes of cryptographic interest. Our generator allowed agile optimization of SQIsign’s NIST PQC Round 2 submission, improving level 1 verification from 123 Mcycles to only 54 Mcycles, a 2.3x speedup. As an additional case study, we use our generator to improve performance of portable implementations of RFC 7748 by up to 2.2x.

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Publication Details

Journal
IACR Transactions on Cryptographic Hardware and Embedded Systems
Published
2025-09-05
DOI
https://doi.org/10.46586/tches.v2025.i4.588-620
Citations
1
Primary Topic
Numerical methods for differential equations
Type
article
Field-Weighted Citation Impact
2.63
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article

Generation of Fast Finite Field Arithmetic forCortex-M4 with ECDH and SQIsign Applications

Décio Luiz Gazzoni Filho, Jorge Chávez-Saab, Félix Carvalho Rodrigues, Julio López et al.
1 citations
IACR Transactions on Cryptographic Hardware and Embedded Systems
Numerical methods for differential equations
2.63
article

Generation of Fast Finite Field Arithmetic forCortex-M4 with ECDH and SQIsign Applications

Décio Luiz Gazzoni Filho, Jorge Chávez-Saab, Félix Carvalho Rodrigues, Julio López, Michael Scott, Francisco Rodríguez‐Henríquez, Gora Adj, Isaac A. Canales-Martínez
article en
1 citations

Abstract

Finite field arithmetic is central to several cryptographic algorithms on embedded devices like the ARM Cortex-M4, particularly for elliptic curve and isogenybased cryptography. However, rapid algorithm evolution, driven by initiatives such as NIST’s post-quantum standardization, might frequently render hand-optimized implementations obsolete. We address this challenge with m4-modarith, a library generating C code with inline assembly for the Cortex-M4 that rivals custom-tuned assembly, enabling agile development in this ever-changing landscape. Our generated modular multiplications obtains fast performances, competitive with hand-optimized assembly implementations published in the literature, even outperforming some of them for Curve25519. Two contributions are pivotal to this success. First, we introduce a novel multiplication strategy that matches the memory access complexity of the operand caching method while being applicable to a larger cache size for Cortex-M4 implementations. Second, we generalize an efficient pseudo-Mersenne reduction strategy, and formally prove its correctness and applicability for most primes of cryptographic interest. Our generator allowed agile optimization of SQIsign’s NIST PQC Round 2 submission, improving level 1 verification from 123 Mcycles to only 54 Mcycles, a 2.3x speedup. As an additional case study, we use our generator to improve performance of portable implementations of RFC 7748 by up to 2.2x.

IACR Transactions on Cryptographic Hardware and Embedded SystemsVol. 2025(4)
Universidade Estadual de Londrina (BR), Universidade Estadual de Campinas (UNICAMP) (BR), Technology Innovation Institute (AE)
Openalex Percentile: Top 10%
Numerical methods for differential equations
2.63
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