Issue |
RAIRO-Theor. Inf. Appl.
Volume 59, 2025
|
|
---|---|---|
Article Number | 2 | |
Number of page(s) | 14 | |
DOI | https://doi.org/10.1051/ita/2025001 | |
Published online | 28 July 2025 |
Image encryption using novel chaotic map and cellular automata dynamics
Department of Mathematics, College of Engineering and Technology, SRM Institute of Science and Technology,
Kattankulathur
603203,
India
* Corresponding author: venkater1@srmist.edu.in
Received:
18
October
2023
Accepted:
2
July
2025
The rapid growth of online information transmission has made the secure transmission and storage of sensitive visual information crucial, particularly in light of the continuous increase in cyber threats. Traditional encryption algorithms are not very effective on images due to their very high pixel correlation, larger file sizes, and intrinsic redundancy. This paper presents a new framework of secure image encryption that will make use of advanced chaotic maps and cellular automata dynamics. It creates deterministic randomness, high sensitivity to initial conditions, and unpredictability through chaotic maps. CA introduces a series of dynamic, rule-based transformations that ensure robust properties for diffusion and confusion. During encryption, chaotic maps create pseudo-random sequences that control both the CA-based pixel scrambling and value transformation. This provides a very secure encryption method with many layers. It ensures high entropy in key generation, resistance against brute-force attacks, and high sensitivity to initial parameters. The scheme works because it can withstand differential, statistical, and noise-based attacks and show performance metrics like entropy analysis, correlation coefficients, histogram uniformity, and robustness. The suggested method is characterized by large-scale use, adaptability, and safety from modern cryptographic threats.
Mathematics Subject Classification: 37B15 / 68Q80 / 68P25
Key words: Cellular automata / crptography / image encryption / decryption / chaotic map
© The authors. Published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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