Backtracking Search for Optimal Parameters of a PLL-based True Random Number Generator
Brice Colombiera, Nathalie Bochardb, Florent Bernardc and Lilian Bossuetd
Univ Lyon, UJM-Saint-Etienne, CNRS, Laboratoire Hubert Curien UMR 5516, F-42023, SAINT- ÉTIENNE, France
ab.colombier@univ-st-etienne.fr
bnathalie.bochard@univ-st-etienne.fr
cflorent.bernard@univ-st-etienne.fr
dlilian.bossuet@univ-st-etienne.fr
ABSTRACT
The phase-locked loop-based true random number generator (PLL-TRNG) extracts randomness from clock jitter. It is an interesting construct because it comes with a stochastic model, making it certifiable by certification bodies. However, bringing it to good performance is difficult since it comes with multiple parameters to tune. This article proposes to use backtracking to determine these parameters. Compared to existing methods, based on genetic algorithms or exhaustive search of a feasible set of parameters, backtracking has several advantages. Indeed, since this method is expressible by constraint programming, it provides very good readability. Constraints can be specified in a very straightforward and maintainable way. It also exhibits good performance and generates PLL-TRNG configurations rapidly. Finally, it allows to integrate new exploratory design constraints for the PLL-TRNG very easily. We provide experimental results with a PLL-TRNG implemented on three FPGA families that come with different physical constraints, showing that the method allows to find good parameters for every one of them. Moreover, we were able to obtain configurations that lead to an increase 59% in throughput and 82% in jitter sensitivity on average, thereby generating random numbers of higher quality at a faster rate. This approach also paves the way for new design exploration strategies for PLL-TRNG. The source code of our implementation is open source and available online for reproducibility and reuse.
