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A novel true random number generator based on a stochastic diffusive memristor
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...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5638922/ https://www.ncbi.nlm.nih.gov/pubmed/29026110 http://dx.doi.org/10.1038/s41467-017-00869-x |
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author | Jiang, Hao Belkin, Daniel Savel’ev, Sergey E. Lin, Siyan Wang, Zhongrui Li, Yunning Joshi, Saumil Midya, Rivu Li, Can Rao, Mingyi Barnell, Mark Wu, Qing Yang, J. Joshua Xia, Qiangfei |
author_facet | Jiang, Hao Belkin, Daniel Savel’ev, Sergey E. Lin, Siyan Wang, Zhongrui Li, Yunning Joshi, Saumil Midya, Rivu Li, Can Rao, Mingyi Barnell, Mark Wu, Qing Yang, J. Joshua Xia, Qiangfei |
author_sort | Jiang, Hao |
collection | PubMed |
description | 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:SiO(2) 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. |
format | Online Article Text |
id | pubmed-5638922 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-56389222017-10-17 A novel true random number generator based on a stochastic diffusive memristor Jiang, Hao Belkin, Daniel Savel’ev, Sergey E. Lin, Siyan Wang, Zhongrui Li, Yunning Joshi, Saumil Midya, Rivu Li, Can Rao, Mingyi Barnell, Mark Wu, Qing Yang, J. Joshua Xia, Qiangfei Nat Commun Article 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:SiO(2) 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. Nature Publishing Group UK 2017-10-12 /pmc/articles/PMC5638922/ /pubmed/29026110 http://dx.doi.org/10.1038/s41467-017-00869-x Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Jiang, Hao Belkin, Daniel Savel’ev, Sergey E. Lin, Siyan Wang, Zhongrui Li, Yunning Joshi, Saumil Midya, Rivu Li, Can Rao, Mingyi Barnell, Mark Wu, Qing Yang, J. Joshua Xia, Qiangfei A novel true random number generator based on a stochastic diffusive memristor |
title | A novel true random number generator based on a stochastic diffusive memristor |
title_full | A novel true random number generator based on a stochastic diffusive memristor |
title_fullStr | A novel true random number generator based on a stochastic diffusive memristor |
title_full_unstemmed | A novel true random number generator based on a stochastic diffusive memristor |
title_short | A novel true random number generator based on a stochastic diffusive memristor |
title_sort | novel true random number generator based on a stochastic diffusive memristor |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5638922/ https://www.ncbi.nlm.nih.gov/pubmed/29026110 http://dx.doi.org/10.1038/s41467-017-00869-x |
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