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8 November 2024 SLSS-3D: a robust 3D hyperchaotic map with coupled transformations
Yuhao Zhang, Lichang Xiong, Yuechao Bie
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Proceedings Volume 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024); 134163Y (2024) https://doi.org/10.1117/12.3049810
Event: 2024 4th International Conference on Advanced Algorithms and Neural Networks, 2024, Qingdao, China
Abstract
Chaotic systems, known for their unique dynamics, are used in cryptography, neural networks, control engineering, and secure communications. However, some classical and improved hyperchaotic systems may have security issues due to insufficient complexity. To address this problem, this study proposes a novel 3D hyperchaotic map named SLSS-3D. The SLSS-3D system derives from classical logistic, sine, and ICMIC maps through nonlinear coupling transformations. It includes two control parameters, α and β, offering a wider range of parameter selection. This enhances resistance to bruteforce attacks. This study evaluates the hyperchaotic behavior of the SLSS-3D system through analyses of phase diagrams, bifurcation diagrams, Lyapunov exponent spectra, sample entropy, the 0-1 test, and permutation entropy. The findings reveal that the SLSS-3D system demonstrates superior stability and significant chaotic properties. These characteristics suggest that SLSS-3D has substantial potential for applications in cryptography, artificial intelligence, and secure communications.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Yuhao Zhang, Lichang Xiong, and Yuechao Bie "SLSS-3D: a robust 3D hyperchaotic map with coupled transformations", Proc. SPIE 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024), 134163Y (8 November 2024); https://doi.org/10.1117/12.3049810
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KEYWORDS
Complex systems
Control systems
Image encryption
Telecommunications
Artificial intelligence
Computer security
Computing systems
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