A novel true random number generator based on a stochastic diffusive memristor
journal contributionposted on 28.09.2017, 15:47 by Hao Jiang, Daniel Belkin, Sergey SavelievSergey Saveliev, Siyan Lin, Zhongrui Wang, Yunning Li, Saumil Joshi, Rivu Midya, Can Li, Mingyi Rao, Mark Barnell, Qing Wu, J. Joshua Yang, Qiangfei Xia
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).
This work was supported in part by the U.S. Air Force Office for Scientific Research (AFOSR) (Grant No. FA9550-12-1-0038), the U.S. Air Force Research Laboratory (AFRL) (Grant No. FA8750-15-2-0044), and the National Science Foundation (NSF; ECCS-1253073). D.B. is supported by a Research Experience for Undergraduates (REU) supplement grant from NSF.