Paper 2016/1091

On the Entropy of Oscillator-Based True Random Number Generators

Yuan Ma, Jingqiang Lin, and Jiwu Jing


True random number generators (TRNGs) are essential for cryptographic systems, and they are usually evaluated by the concept of entropy. In general, the entropy of a TRNG is estimated from its stochastic model, and reflected in the statistical results of the generated raw bits. Oscillator-based TRNGs are widely used in practical cryptographic systems due to its elegant structure, and its stochastic model has been studied in different aspects. In this paper, we investigate the applicability of the different entropy estimation methods for oscillator-based TRNGs, including the bit-rate entropy, the lower bound and the approx imate entropy. Particularly, we firstly analyze the two existing stochastic models (one of which is phase-based and the other is time-based), and deduce consistent bit-rate entropy results from these two models. Then, we design an approximate entropy calculation method on the output raw bits of a simulated oscillator-based TRNG, and this statistical calculation result well matches the bit-rate entropy from stochastic models. In addition, we discuss the extreme case of tiny randomness where some methods are inapplicable, and provide the recommendations for these entropy evaluation methods. Finally, we design a hardware verification method in a real oscillator-based TRNG, and validate these estimation methods in the hardware platform.

Available format(s)
Publication info
Published elsewhere. Minor revision. CT-RSA 2017
Oscillatorstrue random number generatorsentropy estimationstochastic model
Contact author(s)
yma @ lois cn
2016-11-22: received
Short URL
Creative Commons Attribution


      author = {Yuan Ma and Jingqiang Lin and Jiwu Jing},
      title = {On the Entropy of Oscillator-Based True Random Number Generators},
      howpublished = {Cryptology ePrint Archive, Paper 2016/1091},
      year = {2016},
      note = {\url{}},
      url = {}
Note: In order to protect the privacy of readers, does not use cookies or embedded third party content.