Practical Implementation of a Deep Random Generator
This work addresses the need for unconditionally secure communication protocols by providing practical implementations of deep randomness, though it appears incremental as it builds on prior theoretical concepts.
The paper tackles the practical implementation of a Deep Random Generator, which produces randomness with unpredictable results and unknown distributions, by presenting two algorithmic methods for classical computing and discussing their performance and parameters.
We have introduced in former work the concept of Deep Randomness and its interest to design Unconditionally Secure communication protocols. We have in particular given an example of such protocol and introduced how to design a Deep Random Generator associated to that protocol. Deep Randomness is a form of randomness in which, at each draw of random variable, not only the result is unpredictable bu also the distribution is unknown to any observer. In this article, we remind formal definition of Deep Randomness, and we expose two practical algorithmic methods to implement a Deep Random Generator within a classical computing resource. We also discuss their performances and their parameters.