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Entropy Sources Based on Silicon Chips: True Random Number Generator and Physical Unclonable Function
Entropy is a measure of uncertainty or randomness. It is the foundation for almost all cryptographic systems. True random number generators (TRNGs) and physical unclonable functions (PUFs) are the silicon primitives to respectively harvest dynamic and static entropy to generate random bit streams. I...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689501/ https://www.ncbi.nlm.nih.gov/pubmed/36359655 http://dx.doi.org/10.3390/e24111566 |
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author | Cao, Yuan Liu, Wanyi Qin, Lan Liu, Bingqiang Chen, Shuai Ye, Jing Xia, Xianzhao Wang, Chao |
author_facet | Cao, Yuan Liu, Wanyi Qin, Lan Liu, Bingqiang Chen, Shuai Ye, Jing Xia, Xianzhao Wang, Chao |
author_sort | Cao, Yuan |
collection | PubMed |
description | Entropy is a measure of uncertainty or randomness. It is the foundation for almost all cryptographic systems. True random number generators (TRNGs) and physical unclonable functions (PUFs) are the silicon primitives to respectively harvest dynamic and static entropy to generate random bit streams. In this survey paper, we present a systematic and comprehensive review of different state-of-the-art methods to harvest entropy from silicon-based devices, including the implementations, applications, and the security of the designs. Furthermore, we conclude the trends of the entropy source design to point out the current spots of entropy harvesting. |
format | Online Article Text |
id | pubmed-9689501 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96895012022-11-25 Entropy Sources Based on Silicon Chips: True Random Number Generator and Physical Unclonable Function Cao, Yuan Liu, Wanyi Qin, Lan Liu, Bingqiang Chen, Shuai Ye, Jing Xia, Xianzhao Wang, Chao Entropy (Basel) Review Entropy is a measure of uncertainty or randomness. It is the foundation for almost all cryptographic systems. True random number generators (TRNGs) and physical unclonable functions (PUFs) are the silicon primitives to respectively harvest dynamic and static entropy to generate random bit streams. In this survey paper, we present a systematic and comprehensive review of different state-of-the-art methods to harvest entropy from silicon-based devices, including the implementations, applications, and the security of the designs. Furthermore, we conclude the trends of the entropy source design to point out the current spots of entropy harvesting. MDPI 2022-10-30 /pmc/articles/PMC9689501/ /pubmed/36359655 http://dx.doi.org/10.3390/e24111566 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Cao, Yuan Liu, Wanyi Qin, Lan Liu, Bingqiang Chen, Shuai Ye, Jing Xia, Xianzhao Wang, Chao Entropy Sources Based on Silicon Chips: True Random Number Generator and Physical Unclonable Function |
title | Entropy Sources Based on Silicon Chips: True Random Number Generator and Physical Unclonable Function |
title_full | Entropy Sources Based on Silicon Chips: True Random Number Generator and Physical Unclonable Function |
title_fullStr | Entropy Sources Based on Silicon Chips: True Random Number Generator and Physical Unclonable Function |
title_full_unstemmed | Entropy Sources Based on Silicon Chips: True Random Number Generator and Physical Unclonable Function |
title_short | Entropy Sources Based on Silicon Chips: True Random Number Generator and Physical Unclonable Function |
title_sort | entropy sources based on silicon chips: true random number generator and physical unclonable function |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689501/ https://www.ncbi.nlm.nih.gov/pubmed/36359655 http://dx.doi.org/10.3390/e24111566 |
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