A novel true random number generator based on a stochastic diffusive memristor. Issue 1 (December 2017)

• Record Type: Journal Article
• Authors: Jiang, Hao; Belkin, Daniel; Savel'ev, Sergey; Lin, Siyan; Wang, Zhongrui; Li, Yunning; Joshi, Saumil; Midya, Rivu; Li, Can; Rao, Mingyi; Barnell, Mark; Wu, Qing; Yang, J.; Xia, Qiangfei
• Is Part Of: Nature communications. Volume 8:Issue 1(2017)
• Page Start: 1
• Page End: 9
• Publication Date: 2017-12
• Subjects: Biology -- Periodicals; Physical sciences -- Periodicals; 505
• DOI: 10.1038/s41467-017-00869-x
• Languages: English
• ISSNs: 2041-1723

Abstract

Abstract The intrinsic variability of switching behavior in memristors has been a major obstacle to their adoption as the next generation of 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 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 true random number generator pass all 15 NIST randomness tests without any post-processing, a first for memristive-switching true random number generators. Based on nanoparticle dynamic simulation and analytical estimates, we attribute 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 the Internet of Things. Memristors can switch between high and low electrical-resistance states, but the switching behaviour can be unpredictable. Here, the authors harness this unpredictability to develop a memristor-based true random number generator that uses the stochastic delay time of threshold switching