Abstract

This paper focuses on high-speed NEON-based constant-time implementations of multiplication of large polynomials in the NIST PQC KEM Finalists: NTRU, Saber, and CRYSTALS-Kyber. We use the Number Theoretic Transform (NTT)-based multiplication in Kyber, the Toom-Cook algorithm in NTRU, and both types of multiplication in Saber. Following these algorithms and using Apple M1, we improve the decapsulation performance of the NTRU, Kyber, and Saber-based KEMs at the security level 3 by the factors of 8.4, 3.0, and 1.6, respectively, compared to the reference implementations. On Cortex-A72, we achieve the speed-ups by factors varying between 5.7 and 7.5 $$\times $$ for the Forward/Inverse NTT in Kyber, and between 6.0 and 7.8 $$\times $$ for Toom-Cook in NTRU, over the best existing implementations in pure C. For Saber, when using NEON instructions on Cortex-A72, the implementation based on NTT outperforms the implementation based on the Toom-Cook algorithm by $$14\%$$ in the case of the MatrixVectorMul function but is slower by $$21\%$$ in the case of the InnerProduct function. Taking into account that in Saber, keys are not available in the NTT domain, the overall performance of the NTT-based version is very close to the performance of the Toom-Cook version. The differences for the entire decapsulation at the three major security levels (1, 3, and 5) are $$-4$$ , $$-2$$ , and $$+2\%$$ , respectively. Our benchmarking results demonstrate that our NEON-based implementations run on an Apple M1 ARM processor are comparable to those obtained using the best AVX2-based implementations run on an AMD EPYC 7742 processor. Our work is the first NEON-based ARMv8 implementation of each of the three NIST PQC KEM finalists.

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