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Hybrid Chaotic Based PRNG for Secure Cryptography Applications
Version 1
: Received: 25 April 2023 / Approved: 26 April 2023 / Online: 26 April 2023 (09:06:21 CEST)
A peer-reviewed article of this Preprint also exists.
Alnajim, A.M.; Abou-Bakr, E.; Alruwisan, S.S.; Khan, S.; Elmanfaloty, R.A. Hybrid Chaotic-Based PRNG for Secure Cryptography Applications. Appl. Sci. 2023, 13, 7768. Alnajim, A.M.; Abou-Bakr, E.; Alruwisan, S.S.; Khan, S.; Elmanfaloty, R.A. Hybrid Chaotic-Based PRNG for Secure Cryptography Applications. Appl. Sci. 2023, 13, 7768.
Abstract
This paper suggests a novel one-dimensional (1D) map to address the limitations of traditional chaotic 1D maps. The main challenge with traditional chaotic 1D maps is the limited control parameter range and the potential risk of collapsing as a result under the finite precision implementation. To overcome these limitations, the new 1D map hybridises the traditional logistic map with tent map, and a linear tent-like function. This hybridization results in a wider range of control parameters to produce chaotic behavior. The dynamic behavior of the new 1D map has been analyzed using well known numerical methods, including the bifurcation diagram and Lyapunov exponent. Both tests have shown their complex and diverse behavior. In addition, a novel image encryption scheme has been devised using the new function as its pseudo-random-number generator. The proposed encryption algorithm has been tested and found to be robust and secure, passing all statistical tests applied to the encrypted images. The results of this study demonstrate the effectiveness of the new 1D map for use in secure image cryptography applications, providing a more robust and secure alternative to traditional chaotic 1D maps. The proposed algorithm has demonstrated high performance in NPCR and UACI tests. It also has shown good results in the MSE and PSNR tests.
Keywords
Chaos; Encryption; SHA-256; NPCR; UACI
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
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.
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