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Efficient Software Implementation of Ring-LWE Encryption on IoT Processors

机译:IOT处理器上环-LWE加密的高效软件实现

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摘要

Embedded processors have been widely used for building up Internet of Things (IoT) platforms, in which the security issue is becoming critical. This paper studies efficient techniques of lattice-based cryptography on these processors and presents the first implementation of ring-LWE encryption on ARM NEON and MSP430 architectures. For ARM NEON architecture, we propose a vectorized version of Iterative Number Theoretic Transform (NTT) for high-speed computation of polynomial multiplication on ARM NEON platforms and a 32-bit variant of SAMS2 technique for fast reduction. For MSP430 architecture, we propose an optimized SWAMS2 reduction technique, which consists of five different basic operations, including Shifting, Swapping, Addition, and two Multiplication-Subtractions. Regarding of the sampling from the discrete Gaussian distribution, we adopt Knuth-Yao sampler, accompanied with optimized methods such as Look-Up Table (LUT) and byte-scanning. Subsequently, a full-fledged implementation of Ring-LWE is presented by both taking advantage of our proposed method and previous optimization techniques re-designed for desired platforms. Our ring-LWE implementation of encryption/decryption at a classical security level of 128 bits requires only 149:4k/32:8k clock cycles on ARM NEON, and 2126:3k/244:5k clock cycles on MSP430. These results are roughly 7 times faster than the fastest ECC implementation on desired platforms with same security level.
机译:嵌入式处理器已广泛用于构建事物(IOT)平台的互联网,其中安全问题正变得危急。本文研究了这些处理器对这些处理器的晶格类密码技术的有效技术,并在ARM Neon和MSP430架构上提供了Ring-LWE加密的第一次实现。对于ARM NEON架构,我们提出了一种矢量化版本的迭代编号理论变换(NTT),用于ARM霓虹灯平台上多项式乘法的高速计算和SAMS2技术的32位变体,以便快速减少。对于MSP430架构,我们提出了一种优化的SWAMS2减少技术,该技术由五种不同的基本操作组成,包括转换,交换,加法和两个乘法减法。关于从离散高斯分布的采样,我们采用Knuth-yao采样器,伴随着优化的方法,如查找表(LUT)和字节扫描。随后,通过利用我们所提出的方法和以前的优化技术来介绍了Ring-LWE的全掉的实施方式,并为所需平台重新设计。我们的Ring-LWE在传统安全级别的加密/解密的实施中只需要149:4K / 32:8K时钟周期,以及MSP430上的2126:3K / 244:5K时钟周期。这些结果比具有相同安全级别的所需平台上最快的ECC实现速度快7倍。

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