Testing and selecting lightweight pseudo-random number generators for IoT devices

Author(s):  
Augusto Parisot ◽  
Lucila M. S. Bento ◽  
Raphael C. S. Machado
2022 ◽  
Vol 4 (2) ◽  
Author(s):  
Unsub Zia ◽  
Mark McCartney ◽  
Bryan Scotney ◽  
Jorge Martinez ◽  
Ali Sajjad

AbstractPseudo-random number generators (PRNGs) are one of the building blocks of cryptographic methods and therefore, new and improved PRNGs are continuously developed. In this study, a novel method to generate pseudo-random sequences using coupled map lattices is presented. Chaotic maps only show their chaotic behaviour for a specified range of control parameters, what can restrict their application in cryptography. In this work, generalised symmetric maps with adaptive control parameter are presented. This novel idea allows the user to choose any symmetric chaotic map, while ensuring that the output is a stream of independent and random sequences. Furthermore, to increase the complexity of the generated sequences, a lattice-based structure where every local map is linked to its neighbouring node via coupling factor has been used. The dynamic behaviour and randomness of the proposed system has been studied using Kolmogorov–Sinai entropy, bifurcation diagrams and the NIST statistical suite for randomness. Experimental results show that the proposed PRNG provides a large key space, generates pseudo-random sequences and is computationally suitable for IoT devices.


2017 ◽  
Vol 90 (3) ◽  
pp. 1661-1670 ◽  
Author(s):  
Luis Gerardo de la Fraga ◽  
Esteban Torres-Pérez ◽  
Esteban Tlelo-Cuautle ◽  
Cuauhtemoc Mancillas-López

1992 ◽  
Vol 5 (4) ◽  
pp. 291-305 ◽  
Author(s):  
D. Ugrin-Šparac

The renewal process generated by the uniform distribution, when interpreted as a transformation of the uniform distribution into a discrete distribution, gives rise to the question of uniqueness of the inverse image. The paper deals with a particular problem from the described domain, that arose in the construction of a complex stochastic test intended to evaluate pseudo-random number generators. The connection of the treated problem with the question of a unique integral representation of Gamma-function is also mentioned.


MENDEL ◽  
2018 ◽  
Vol 24 (2) ◽  
Author(s):  
Tomas Brandejsky

This paper analyses the influence of experiment parameters onto the reliability of experiments with genetic programming algorithms. The paper is focused on the required number of experiments and especially on the influence of parallel execution which affect not only the order of thread execution but also behaviors of pseudo random number generators, which frequently do not respect recommendation of C++11 standard and are not implemented as thread safe. The observations and the effect of the suggested improvements are demonstrated on results of 720,000 experiments.


Sign in / Sign up

Export Citation Format

Share Document