A Physical Approach for Stochastic Modeling of TERO-based TRNG

International audienceSecurity in random number generation for cryptography is closely related to the entropy rate at the generator output. This rate has to be evaluated using an appropriate stochastic model. The stochastic model proposed in this paper is dedicated to the transition effect ring oscillator (TERO) based true random number generator (TRNG) proposed by Varchola and Drutarovsky in 2010. The advantage and originality of this model is that it is derived from a physical model based on a detailed study and on the precise electrical description of the noisy physical phenomena that contribute to the generation of random numbers. We compare the proposed electrical description with data generated in a 28 nm CMOS ASIC implementation. Our experimental results are in very good agreement with those obtained with both the physical model of TERO's noisy behavior and with the stochastic model of the TERO TRNG, which we also confirmed using the AIS 31 test suites

Jitter Estimation with High Accuracy for Oscillator-Based TRNGs

Ring oscillator-based true random number generators (RO-based TRNGs) are widely used to provide unpredictable random numbers for cryptographic systems. The unpredictability of the output numbers, which can be measured by entropy, is extracted from the jitter of the oscillatory signal. To quantitatively evaluate the entropy, several stochastic models have been proposed, all of which take the jitter as a key input parameter. So it is crucial to accurately estimate the jitter in the process of entropy evaluation. However, several previous methods have estimated the jitter with non-negligible error, which would cause the overestimation of the entropy. In this paper, we propose a jitter estimation method with high accuracy. Our method aims at eliminating the quantization error in previous counter-based jitter estimation methods and finally can estimate the jitter with the error smaller than $1\%$. Furthermore, for the first time, we give a theoretical error bound for our jitter estimation. The error bound confirms the $1\%$ error level of our method. As a consequence, our method will signicantly help to evaluate the entropy of RO-based TRNGs accurately. Finally, we present the application of our jitter estimation method on a practical FPGA device and provide a circuit module diagram for on-chip implementation

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