基于多相采样MUX单元熵的轻量级M_TRNG设计

Liang Yao, Huaguo Liang, Hong Zhang, Tianming Ni, Maoxiang Yi, Yingchun Lu
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引用次数: 0

摘要

真随机数生成器(True Random Number Generator, TRNG)是基于硬件的非确定性噪声构建的,用于在各种需要加密保护的应用程序中生成密钥、初始化向量和随机数。本文通过对频率抖动机理的研究,提出了一种基于MUX单元多相采样的真随机数发生器。该方案基于MUX单元的“软宏”设计,取代了传统的查表熵方案。它在保证TRNG熵源公平性的基础上完成了高精度的抖动采样,并且可以很好地移植到一系列fpga上。提出的TRNG在Xilinx Virtex-6、Artix-7和Virtex-7三个fpga上进行了验证。实验结果表明,生成的随机序列质量较好,以较高的p值通过了NIST SP800-22测试,以较高的最小熵通过了NIST SP 800-90B测试,吞吐量达到100Mbps。值得一提的是,所提出的TRNG所消耗的资源开销小且单一,仅消耗4个MUX单元、4个dff和1个LUT单元,具有良好的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Lightweight M_TRNG Design based on MUX Cell Entropy using Multiphase Sampling
True Random Number Generator (TRNG) is built on hardware-based non-deterministic noise for generating keys, initialization vectors, and random numbers in a variety of applications requiring cryptographic protection. In this paper, through the research of frequency jitter mechanism, a true random number generator based on multi-phase sampling of MUX unit is proposed. The scheme is based on the “soft macro” design of the MUX unit, which replaces the traditional look-up table entropy scheme. It completes high-precision jitter sampling on the basis of ensuring the fairness of the TRNG entropy source, and can be well transplanted to a series of FPGAs. The proposed TRNG is verified on three FPGAs of Xilinx Virtex-6, Artix-7 and Virtex-7. The experimental results show that the generated random sequences are of good quality, passing the NIST SP800-22 tests with higher p-value and passing NIST SP 800-90B tests with higher minimum entropy, while achieving 100Mbps throughput. It is worth mentioning that the resource overhead consumed by the proposed TRNG is small and single, only consuming 4 MUX units, 4 DFFs and one LUT unit, which has a good application prospect.
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