We discuss a monitoring system aiming to select, among a set of integrated entropy sources affected by process variability, the source guarantying the highest worst-case entropy. The approach is particularly suitable when considering True Random Number Generators based on Digital Nonlinear Oscillators, since multiple instances of the entropy sources can be implemented at a reduced hardware cost. In general, the approach can be applied for TRNGs based on parametric systems, thus offering entropy tuning capabilities. The original theoretical results have been validated with experiments.
A Low-Complexity Method to Address Process Variability in True Random Number Generators based on Digital Nonlinear Oscillators
Papini D.
2022-01-01
Abstract
We discuss a monitoring system aiming to select, among a set of integrated entropy sources affected by process variability, the source guarantying the highest worst-case entropy. The approach is particularly suitable when considering True Random Number Generators based on Digital Nonlinear Oscillators, since multiple instances of the entropy sources can be implemented at a reduced hardware cost. In general, the approach can be applied for TRNGs based on parametric systems, thus offering entropy tuning capabilities. The original theoretical results have been validated with experiments.File in questo prodotto:
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