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Design of New Chaotic System with Hyperbolic Sine Function based on Pseudo-Random Number Generation for Medical Image Encryption

Rameshbabu RamarDepartment of Electronics and Communication Engineering, V.S.B. Engineering College, Karur, 639111, Tamil Nadu, IndiaAceng SambasArtificial Intelligence for Sustainability and Islamic Research Center (AIRIS), Universiti Sultan Zainal Abidin, Gongbadak, Terengganu, 21300, MalaysiaSezgin KaçarDepartment of Electrical and Electronics Engineering, Sakarya University of Applied Sciences, Serdivan, 54050, Sakarya, TurkeyKarimov Javlon KuzievichDepartment of Higher and Applied Mathematics, Tashkent State University of Economics, Tashkent, UzbekistanIbrahim Mohammed SulaimanFaculty of Education and Arts, Sohar University, Sohar, 311, OmanMehmet OrdukayaDepartment of Electrical and Electronics Engineering, Graduate Education Institute, Sakarya University of Applied Sciences, Serdivan, 54050, Sakarya, TurkeyMuhammed TelçekenComputer Engineering, Institute of Natural Sciences, Serdivan, 54050, Sakarya, Turkey
ABI

Аннотация

This study presents the development of a novel three-dimensional chaotic system incorporating a hyperbolic sine function, characterized by its chaotic dynamics and applications in pseudo-random number generation (PRNG) for medical image encryption. Our system exhibiting rotational symmetry under a $$180^{\circ }$$ transformation about the z-axis. Dynamical analyses, including bifurcation diagrams and Lyapunov spectrum evaluations, confirm multistability and coexistence of periodic and chaotic attractors. As an engineering application, a PRNG based on the system is implemented for medical image encryption. The PRNG passes all NIST-800-22 statistical tests, achieving high randomness with test results ranging between 0.001 and 1. Image encryption is tested on head and chest images, yielding statistical metrics such as entropy (79.566 and 79.576), contrast (105.163 and 104.860), and encryption quality (28004 and 25800), demonstrating the robustness and reliability of the proposed approach. This work offers a promising tool for secure medical image processing with high computational efficiency.

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