International Association for Cryptologic Research

International Association
for Cryptologic Research


Patrick Haddad


Low Cost and Precise Jitter Measurement Method for TRNG Entropy Assessment
Random number generators and specifically true random number generators (TRNGs) are essential in cryptography. TRNGs implemented in logic devices usually exploit the time instability of clock signals generated in freely running oscillators as source of randomness. To assess the performance and quality of oscillator-based TRNGs, accurate measurement of clock jitter originating from thermal noise is of paramount importance. We propose a novel jitter measurement method, in which the required jitter accumulation time can be reduced to around 100 reference clock periods. Reduction of the jitter accumulation time reduces the impact of the flicker noise on the measured jitter and increases the precision of the estimated contribution of thermal noise. In addition, the method can be easily embedded in logic devices. The fact that the jitter measurement can be placed in the same device as the TRNG is important since it can be used as a basis for efficient embedded statistical tests. In contrast to other methods, we propose a thorough theoretical analysis of the measurement error. This makes it possible to tune the parameters of the method to guarantee a relative error smaller than 12% even in the worst cases.
From Physical to Stochastic Modeling of a TERO-Based TRNG
Security 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: Cryptographic hardware and embedded systems (CHES), 2010, Springer, 2010 ). The advantage and originality of this model are 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 two different technologies: TERO TRNG implementations in 40 and 28 nm CMOS ASICs. Our experimental results are in very good agreement with those obtained with both the physical model of TERO’s noisy behavior and the stochastic model of the TERO TRNG, which we also confirmed using the AIS 31 test suites.