Abstract
We discuss a stochastic algorithm to design tuning controllers for cryptographic True Random Number Generators, compliant to NIST recommendations, as an effective low-complexity solution to counteract entropy variability in integrated architectures implementing tunable entropy sources. Taking as a reference the min-entropy concept, we discussed the proposal from both the theoretical and hardware design points of view, validating claims with proofs and experiments. Depending on the target accuracy, the proposed architecture is scalable, and its profitable use in TRNG design strongly depends on the kind of core entropy sources taken into account. Furthermore, we show that the low-complexity entropy measurement techniques exploited in this proposal can be used to design a legitimate alternative to the Adaptive Proportion Health Test recommended in the NIST 800.90B publication.
Highlights
We have discussed a stochastic algorithm to design tuning controllers for cryptographic True Random Number Generators, compliant to National Institute of Standards and Technology (NIST) recommendations, as an effective low-complexity solution to counteract entropy variability in integrated architectures implementing tunable entropy sources
Taking as a reference the min-entropy concept introduced by NIST, we discussed the proposal from both the theoretical and hardware design points of view, validating claims with proofs and experiments
Depending on the target accuracy, the proposed solution is scalable, and its profitable use in True Random Number Generators (TRNGs) design strongly depends on the kind of core entropy sources taken into account
Summary
True Random Number Generators (TRNGs) are integrated circuits devised to generate sequences of truly random bits. Depending on the design of the TRNG core, the technical relation between entropy and tuning/controlling parameters can be strongly dependent on the implementation This happens, e.g., in some fully digital TRNGs combining complex oscillators and metastable circuits, in which process-voltage-temperature variations can play relevant roles [13]–[17], [30]–[32]. Adopting a well-defined theoretical framework, our proposal is based on estimation methods exploiting low-complexity entropy measurement techniques, and has a generic validity
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call