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Random-telegraph-noise-enabled true random number generator for hardware security
The future security of Internet of Things is a key concern in the cyber-security field. One of the key issues is the ability to generate random numbers with strict power and area constrains. “True Random Number Generators” have been presented as a potential solution to this problem but improvements...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7560754/ https://www.ncbi.nlm.nih.gov/pubmed/33057091 http://dx.doi.org/10.1038/s41598-020-74351-y |
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author | Brown, James Zhang, Jian Fu Zhou, Bo Mehedi, Mehzabeen Freitas, Pedro Marsland, John Ji, Zhigang |
author_facet | Brown, James Zhang, Jian Fu Zhou, Bo Mehedi, Mehzabeen Freitas, Pedro Marsland, John Ji, Zhigang |
author_sort | Brown, James |
collection | PubMed |
description | The future security of Internet of Things is a key concern in the cyber-security field. One of the key issues is the ability to generate random numbers with strict power and area constrains. “True Random Number Generators” have been presented as a potential solution to this problem but improvements in output bit rate, power consumption, and design complexity must be made. In this work we present a novel and experimentally verified “True Random Number Generator” that uses exclusively conventional CMOS technology as well as offering key improvements over previous designs in complexity, output bitrate, and power consumption. It uses the inherent randomness of telegraph noise in the channel current of a single CMOS transistor as an entropy source. For the first time multi-level and abnormal telegraph noise can be utilised, which greatly reduces device selectivity and offers much greater bitrates. The design is verified using a breadboard and FPGA proof of concept circuit and passes all 15 of the NIST randomness tests without any need for post-processing of the generated bitstream. The design also shows resilience against machine learning attacks performed by the LSTM neural network. |
format | Online Article Text |
id | pubmed-7560754 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75607542020-10-19 Random-telegraph-noise-enabled true random number generator for hardware security Brown, James Zhang, Jian Fu Zhou, Bo Mehedi, Mehzabeen Freitas, Pedro Marsland, John Ji, Zhigang Sci Rep Article The future security of Internet of Things is a key concern in the cyber-security field. One of the key issues is the ability to generate random numbers with strict power and area constrains. “True Random Number Generators” have been presented as a potential solution to this problem but improvements in output bit rate, power consumption, and design complexity must be made. In this work we present a novel and experimentally verified “True Random Number Generator” that uses exclusively conventional CMOS technology as well as offering key improvements over previous designs in complexity, output bitrate, and power consumption. It uses the inherent randomness of telegraph noise in the channel current of a single CMOS transistor as an entropy source. For the first time multi-level and abnormal telegraph noise can be utilised, which greatly reduces device selectivity and offers much greater bitrates. The design is verified using a breadboard and FPGA proof of concept circuit and passes all 15 of the NIST randomness tests without any need for post-processing of the generated bitstream. The design also shows resilience against machine learning attacks performed by the LSTM neural network. Nature Publishing Group UK 2020-10-14 /pmc/articles/PMC7560754/ /pubmed/33057091 http://dx.doi.org/10.1038/s41598-020-74351-y Text en © The Author(s) 2020 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Brown, James Zhang, Jian Fu Zhou, Bo Mehedi, Mehzabeen Freitas, Pedro Marsland, John Ji, Zhigang Random-telegraph-noise-enabled true random number generator for hardware security |
title | Random-telegraph-noise-enabled true random number generator for hardware security |
title_full | Random-telegraph-noise-enabled true random number generator for hardware security |
title_fullStr | Random-telegraph-noise-enabled true random number generator for hardware security |
title_full_unstemmed | Random-telegraph-noise-enabled true random number generator for hardware security |
title_short | Random-telegraph-noise-enabled true random number generator for hardware security |
title_sort | random-telegraph-noise-enabled true random number generator for hardware security |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7560754/ https://www.ncbi.nlm.nih.gov/pubmed/33057091 http://dx.doi.org/10.1038/s41598-020-74351-y |
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