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An efficient and light weight polynomial multiplication for ideal lattice-based cryptography

机译:基于理想格子的密码学的高效和重量轻的多项式乘法

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摘要

Ring-Learning With Errors (Ring-LWE) based cryptographic schemes such as signature, key exchange, and encryption require polynomial multiplication. This multiplication operation is the most time consuming and computationally rigorous process in Ring-LWE. In order to improve the efficiency of the Ring-LWE based schemes, most of the existing schemes use Fast Fourier Transform (FFT) based polynomial multiplication algorithm. It is known that Discrete Sine Transformation (DST) and Discrete Cosine Transformation (DCT) are faster than the FFT. The combination of DCT and DST is Discrete Trigonometric Transform (DTT). When we generalize DTT in terms of FFT form, it becomes Generalized Discrete Fourier Transform (GDFT). In this paper, we propose two new polynomial multiplication techniques using DTT and GDFT. When we apply circular convolution and skew-circular convolution on DTT or GDFT for the polynomial multiplication, it gives us wrong results. To overcome this issue, we use symmetric convolution operation on DTT and GDFT. We implemented and compared the proposed polynomial multiplication schemes with the current state-of-the-art schemes in terms of computation and communication costs. The implementation results show that the proposed schemes DTT and GDFT perform more efficiently as compared to current state-of-the-art schemes in terms of computation and communication costs.
机译:基于签名,密钥交换和加密的基于错误(Ring-LWE)的密码方案进行响应,需要多项式乘法。该乘法操作是环-LWE中最耗时和计算严格的过程。为了提高基于环-LWE的方案的效率,大多数现有方案使用基于快速的傅里叶变换(FFT)多项式乘法算法。已知离散正弦变换(DST)和离散余弦变换(DCT)比FFT更快。 DCT和DST的组合是离散三角变换(DTT)。当我们以FFT形式概括DTT时,它变成了广义离散傅立叶变换(GDFT)。在本文中,我们提出了使用DTT和GDFT的两种新多项式乘法技术。当我们对多项式乘法的DTT或GDFT应用循环卷积和扭曲循环卷积时,它给了我们错误的结果。为了克服这个问题,我们在DTT和GDFT上使用对称卷积操作。我们在计算和通信成本方面实施了并将所提出的多项式乘法方案与当前的最先进方案进行了比较。实施结果表明,与当前最先进的方案相比,所提出的方案DTT和GDFT在计算和通信成本方面比较更有效地执行。

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