Entropy extraction in metastability-based TRNG

Vikram B. Suresh, W. Burleson
{"title":"Entropy extraction in metastability-based TRNG","authors":"Vikram B. Suresh, W. Burleson","doi":"10.1109/HST.2010.5513099","DOIUrl":null,"url":null,"abstract":"True Random Number Generators (TRNG) implemented in deep sub micron (DSM) technologies become biased in bit generation due to process variations and fluctuations in operating conditions. A variety of mechanisms ranging from analog and digital circuit techniques to algorithmic post-processing can be employed to remove bias. In this work we compare the effectiveness of digital post-processing using the XOR function and Von Neumann Corrector with circuit calibration technique for a meta-stability based reference TRNG design. The energy consumption per bit is used as the metric for comparison of the different techniques. The results indicate that the calibration technique is effective for 12% larger process variation than the XOR function and extracts entropy comparable to the Von Neumann Corrector at 56% lesser energy/bit. The analysis thereby demonstrates that circuit calibration provides an efficient tradeoff between entropy and energy/bit for removing bias in lightweight TRNG.","PeriodicalId":6367,"journal":{"name":"2010 IEEE International Symposium on Hardware-Oriented Security and Trust (HOST)","volume":"15 1","pages":"135-140"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"36","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Symposium on Hardware-Oriented Security and Trust (HOST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HST.2010.5513099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 36

Abstract

True Random Number Generators (TRNG) implemented in deep sub micron (DSM) technologies become biased in bit generation due to process variations and fluctuations in operating conditions. A variety of mechanisms ranging from analog and digital circuit techniques to algorithmic post-processing can be employed to remove bias. In this work we compare the effectiveness of digital post-processing using the XOR function and Von Neumann Corrector with circuit calibration technique for a meta-stability based reference TRNG design. The energy consumption per bit is used as the metric for comparison of the different techniques. The results indicate that the calibration technique is effective for 12% larger process variation than the XOR function and extracts entropy comparable to the Von Neumann Corrector at 56% lesser energy/bit. The analysis thereby demonstrates that circuit calibration provides an efficient tradeoff between entropy and energy/bit for removing bias in lightweight TRNG.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于亚稳的TRNG中的熵提取
由于工艺变化和操作条件的波动,在深亚微米(DSM)技术中实现的真随机数发生器(TRNG)在比特生成方面存在偏差。从模拟和数字电路技术到算法后处理的各种机制都可以用来消除偏置。在这项工作中,我们比较了使用异或函数和冯·诺伊曼校正器与电路校准技术的数字后处理的有效性,用于基于亚稳定的参考TRNG设计。每比特的能量消耗被用作比较不同技术的度量。结果表明,与异或函数相比,该校准技术在过程变化大12%的情况下是有效的,并且以比冯·诺伊曼校正器低56%的能量/比特提取与之相当的熵。因此,分析表明,电路校准为消除轻量级TRNG中的偏置提供了熵和能量/比特之间的有效权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Hardware implementations of hash function Luffa Multiplexing methods for power watermarking Side-channel attack resistant ROM-based AES S-Box Entropy-based power attack ExCCel: Exploration of complementary cells for efficient DPA attack resistivity
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1