A spin-based true random number generator exploiting the stochastic precessional switching of nanomagnets
A spin-based true random number generator exploiting the stochastic precessional switching of nanomagnets
复制标题
利用纳米磁体随机进动切换的基于自旋的真随机数发生器
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
S. Rakheja
中科院分区：
文献类型：
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作者：
N. Rangarajan;Arun Parthasarathy;S. Rakheja
在本文中，我们提出了一种基于自旋的真随机数发生器（TRNG），它使用纳米磁体中固有的随机性作为熵的来源。与以前的自旋为基础的TRNG的工作相比，我们专注于在纳米磁体的进动开关策略，以产生一个真正的随机序列。使用NIST SP 800-22测试套件的随机性，我们证明了所提出的TRNG电路的输出是统计随机的99%的置信水平。的过程和温度的变化对设备的影响进行了研究，并表明没有影响的随机性的设备上的质量。为了基准测试TRNG在面积、吞吐量和功率方面的性能，我们使用基于SPICE（具有集成电路强调的仿真程序）的纳米磁体模型，并将它们与45 nm技术节点处的CMOS器件模型联合收割机相结合。所提出的TRNG的吞吐量，功率和面积的足迹被证明是优于现有的国家的最先进的TRNG。我们确定了任务...
In this paper, we propose a spin-based true random number generator (TRNG) that uses the inherent stochasticity in nanomagnets as the source of entropy. In contrast to previous works on spin-based TRNGs, we focus on the precessional switching strategy in nanomagnets to generate a truly random sequence. Using the NIST SP 800-22 test suite for randomness, we demonstrate that the output of the proposed TRNG circuit is statistically random with 99% confidence levels. The effects of process and temperature variability on the device are studied and shown to have no effect on the quality of randomness of the device. To benchmark the performance of the TRNG in terms of area, throughput, and power, we use SPICE (Simulation Program with Integrated Circuit Emphasis)-based models of the nanomagnet and combine them with CMOS device models at the 45 nm technology node. The throughput, power, and area footprints of the proposed TRNG are shown to be better than those of existing state-of-the-art TRNGs. We identify the op...