NDLI: Sequence-Oriented Stochastic Model of RO-TRNGs for Entropy Evaluation

Content Provider	IET Digital Library
Author	Zhu, Shaofeng Xi, Wei Fan, Limin Chen, Hua Chen, Meihui Feng, Dengguo
Abstract	Ring oscillator-based true random number generators (RO-TRNGs) are widely used to generate unpredictable random numbers for cryptographic systems. Entropy is usually adopted to quantitatively measure the unpredictability of a TRNG. There have been several stochastic models such as the time-oriented and phaseoriented ones built to evaluate the entropy of ElementaryRO-TRNGs with single oscillator. However, these models are not suitable for the TRNGs composed of multiple oscillators (Multiple-RO-TRNGs), which can obtain more randomness and higher throughput. Considering this, we propose a sequence-oriented stochastic model for the entropy evaluation of RO-TRNGs, named the first-order stationary Markov source model. This model is extensible for the Multiple-RO-TRNGs. Based on that, we present a detailed method to determine the entropy of Multiple-ROTRNGs. Our proposed model is verified by experiments. Besides, our method can also be a guide to design ROTRNGs with both high entropy and high throughput.
Starting Page	371
Ending Page	377
Page Count	7
ISSN	10224653
Volume Number	29
e-ISSN	20755597
Issue Number	Issue 2, Mar (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/cje/29/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/cje.2019.12.010
Journal	Chinese Journal of Electronics
Publisher Date	2020-03-01
Access Restriction	Open
Rights Holder	© Chinese Institute of Electronics
Subject Keyword	Cryptographic System Digital Arithmetic Method Elementary-RO-TRNG Entropy Entropy Evaluation First-order Stationary Markov Source Model Logic And Switching Circuit Logic Circuit Markov Processes Multiple-RO-TRNG Oscillator Phase-oriented Ones Random Number Generation Random Number Generator Ring Oscillator Sequence-oriented Stochastic Model Stochastic Linearised SCUC Time-oriented Model Unpredictable Random Numbers
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering

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