Entropy evaluation for oscillator-based true random number generators

被引：26

作者：

Ma, Yuan ^{[1
,2
]}

Lin, Jingqiang ^{[1
,2
]}

Chen, Tianyu ^{[1
,2
]}

Xu, Changwei ^{[1
,2
]}

Liu, Zongbin ^{[1
,2
]}

Jing, Jiwu ^{[1
,2
]}

机构：

[1] Data Assurance and Communication Security Research Center, Chinese Academy of Sciences, Beijing, China

[2] State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China

来源：

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | 2014年 / 8731卷

关键词：

Oscillators (electronic) - Entropy - Random number generation - Stochastic systems - Random processes - Computation theory - Cryptography - Number theory;

D O I：

10.1007/978-3-662-44709-3_30

中图分类号：

学科分类号：

摘要：

True random number generators (TRNGs) are crucial to the implementations of cryptographic algorithms and protocols. The quality of randomness directly influences the security of cryptographic systems. Oscillator-based sampling is popular in the design of TRNGs due to its nice properties of elegant structure and high speed. However, the credibility of randomness generated from high-speed oscillator-based TRNGs, especially ring oscillator-based (RO-based) ones, is still in controversy. This is mainly because pseudo-randomness is hardly distinguished from true randomness and RO-based TRNGs are susceptible to external perturbations. In this paper, we present a stochastic model to evaluate the entropy of oscillator-based TRNGs, and then deduce the requirement of design parameters (including the sampling interval) for sufficient entropy per random bit, i.e., to ensure true randomness. Furthermore, we design a jitter measuring circuit to verify the theory, and the theoretical results are confirmed by both the simulation and practical experiments. Finally, e apply the stochastic model to analyze the effect of deterministic perturbations, and demonstrate that the randomness of RO-based TRNGs (under deterministic perturbations) can be overestimated and predicting the random bits could be possible. © International Association for Cryptologic Research 2014.

引用

页码：544 / 561