A novel true random number generator based on a stochastic diffusive memristor
Hao Jiang
Daniel Belkin
Sergey Saveliev
Siyan Lin
Zhongrui Wang
Yunning Li
Saumil Joshi
Rivu Midya
Can Li
Mingyi Rao
Mark Barnell
Qing Wu
J. Joshua Yang
Qiangfei Xia
2134/26734
https://repository.lboro.ac.uk/articles/journal_contribution/A_novel_true_random_number_generator_based_on_a_stochastic_diffusive_memristor/9407729
The intrinsic variability of switching behavior in memristors has been a major obstacle to their adoption as the next generation universal memory. On the other hand, this natural stochasticity can be valuable for hardware security applications. Here we propose and
demonstrate a novel true random number generator (TRNG) utilizing the stochastic delay time of threshold switching in a Ag:SiO2 diffusive memristor, which exhibits evident advantages in scalability, circuit complexity and power consumption. The random bits generated by the diffusive memristor TRNG passed all 15 NIST randomness tests without any post-processing, a first for memristive-switching TRNGs. Based on nanoparticle
dynamic simulation and analytical estimates, we attributed the stochasticity in delay time to the probabilistic process by which Ag particles detach from a Ag reservoir. This work paves the way for memristors in hardware security applications for the era of Internet of
Things (IoT).
2017-09-28 15:47:21
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Physical Sciences not elsewhere classified