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 / Addabbo, T.; Fort, A.; Mugnaini, M.; Moretti, R.; Vignoli, V.; Papini, D.. - 2022-:(2022), pp. 1670-1674. (Intervento presentato al convegno 2022 IEEE International Symposium on Circuits and Systems, ISCAS 2022 tenutosi a usa nel 2022) [10.1109/ISCAS48785.2022.9937869].
A Low-Complexity Method to Address Process Variability in True Random Number Generators based on Digital Nonlinear Oscillators
Papini D.
2022
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.
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