In an IoT framework, large scale decisions are based on the data generated by the IoT sensors for instance we could cite temperature control in a factory, intruder alarm systems in a smart home or emergency doctor call for patients in smart care between others. The concept of Internet of Things (IoT) has dramatically changed the way things used to work, since smart computers are replacing humans in the loop. Experimental results show that the proposed PRNG provides a large key space, generates pseudo-random sequences and is computationally suitable for IoT devices.Ĭomputers have evolved from large calculating machines to smart handheld devices that have revolutionized human lives. 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. 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. 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. In this work, generalised symmetric maps with adaptive control parameter are presented. Chaotic maps only show their chaotic behaviour for a specified range of control parameters, what can restrict their application in cryptography. In this study, a novel method to generate pseudo-random sequences using coupled map lattices is presented.
Pseudo-random number generators (PRNGs) are one of the building blocks of cryptographic methods and therefore, new and improved PRNGs are continuously developed.
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