Practical Implementation of a Deep Random Generator

TL;DR

This paper discusses the formal definition of Deep Randomness, introduces two practical algorithms for implementing Deep Random Generators, and evaluates their performance for secure communication protocols.

Contribution

It provides the first practical algorithms to implement Deep Random Generators within classical computing resources, advancing secure communication methods.

Findings

Two algorithmic methods for Deep Random Generator implementation

Performance analysis of the proposed algorithms

Discussion on parameters affecting Deep Randomness

Abstract

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.