Version 1
: Received: 8 April 2023 / Approved: 10 April 2023 / Online: 10 April 2023 (04:57:30 CEST)
How to cite:
Alexan, W.; Chen, Y.; Por, L.Y.; Gabr, M. Hyperchaotic Maps and the Single Neuron Model: A Novel Framework for Chaos-Based Image Encryption. Preprints2023, 2023040148. https://doi.org/10.20944/preprints202304.0148.v1
Alexan, W.; Chen, Y.; Por, L.Y.; Gabr, M. Hyperchaotic Maps and the Single Neuron Model: A Novel Framework for Chaos-Based Image Encryption. Preprints 2023, 2023040148. https://doi.org/10.20944/preprints202304.0148.v1
Alexan, W.; Chen, Y.; Por, L.Y.; Gabr, M. Hyperchaotic Maps and the Single Neuron Model: A Novel Framework for Chaos-Based Image Encryption. Preprints2023, 2023040148. https://doi.org/10.20944/preprints202304.0148.v1
APA Style
Alexan, W., Chen, Y., Por, L.Y., & Gabr, M. (2023). Hyperchaotic Maps and the Single Neuron Model: A Novel Framework for Chaos-Based Image Encryption. Preprints. https://doi.org/10.20944/preprints202304.0148.v1
Chicago/Turabian Style
Alexan, W., Lip Yee Por and Mohamed Gabr. 2023 "Hyperchaotic Maps and the Single Neuron Model: A Novel Framework for Chaos-Based Image Encryption" Preprints. https://doi.org/10.20944/preprints202304.0148.v1
Abstract
With the explosion of the generation, transmission and sharing of image data over the Internet and other unsecured networks, the need and significance for the development of novel image encryption algorithms is unprecedented. In this research work, we propose a novel framework for image encryption that is based on two hyperchaotic maps, utilized in conjunction with the single neuron model (SNM). The framework entails three successive stages, where in every stage, a substitution box (S-box) is applied, then XORing with an encryption key is carried out. The S-boxes and the encryption keys are generated from the numerical solutions of the hyperchaotic maps and the SNM. The performance of the proposed framework is gauged through a number of metrics, reflecting superior performance and complete asymmetry between the plain images and their encrypted versions. However, the main advantages of this work are: (1) The attained width of the key space; and (2) The achieved efficiency in software implementation. The superior key space of 2^{2551} is the result of employing the two hyperchaotic maps, while the improved efficiency, resulting in an average encryption rate of 8.54 Mbps, is the result of the utilization of the single neuron model, as well as the employment of optimized parallel processing techniques. In addition, the proposed encryption framework is shown to output encrypted images that pass the NIST SP 800 suite.
Keywords
Cryptography; Hyperchaotic maps; Image encryption; NIST; S-box; Single neuron model.
Subject
Computer Science and Mathematics, Security Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
