Towards efficient polynomial multiplication for lattice-based cryptography

Chaohui Du, Guoqiang Bai
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引用次数: 24

Abstract

Ring learning with errors (Ring-LWE) is the basis of various lattice based cryptosystems. The most critical and computationally intensive operation of Ring-LWE based cryptosystems is polynomial multiplication over rings. In this paper, we introduce several optimization techniques to build an efficient polynomial multiplier with the number theoretic transform (NTT). We propose a technique to optimize the bit-reverse operation of NTT and inverse-NTT. With additional optimizations, our polynomial multiplier reduces the required clock cycles from (8n+1.5n lg n) to (2n+1.5n lg n). By exploiting the relationship of the constant factors, our polynomial multiplier is able to reduce the number of constant factors from 4n to 2.5n, which saves about 37.5% ROM storage. In addition, we propose a novel memory access scheme to achieve maximum utilization of the butterfly operator. With these techniques, our polynomial multiplier is capable to perform 57304/26913 polynomial multiplications per second for dimension 256/512 on a Spartan-6 FPGA.
基于格密码的高效多项式乘法研究
带误差环学习(Ring- lwe)是各种基于格的密码系统的基础。基于环lwe的密码系统中最关键和计算量最大的运算是环上的多项式乘法。本文介绍了几种利用数论变换(NTT)构造高效多项式乘法器的优化技术。我们提出了一种优化NTT和逆NTT的位反转操作的技术。通过额外的优化,我们的多项式乘法器将所需的时钟周期从(8n+1.5n lgn)减少到(2n+1.5n lgn)。通过利用常数因子的关系,我们的多项式乘法器能够将常数因子的数量从4n减少到2.5n,节省约37.5%的ROM存储空间。此外,我们还提出了一种新的内存访问方案,以最大限度地利用蝶形算子。使用这些技术,我们的多项式乘法器能够在Spartan-6 FPGA上对维度256/512每秒执行57304/26913次多项式乘法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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