Open AccessSequence‐Oriented Stochastic Model of RO‐TRNGs for Entropy Evaluation
Author(s) -
Zhu Shaofeng,
Xi Wei,
Fan Limin,
Chen Hua,
Chen Meihui,
Feng Dengguo
Publication year - 2020
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2019.12.010
Subject(s) - randomness , random number generation , entropy (arrow of time) , computer science , hidden markov model , algorithm , ring oscillator , markov chain , mathematics , artificial intelligence , machine learning , statistics , engineering , physics , quantum mechanics , voltage , electrical engineering
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.