Elevating Medical Image Security: A Cryptographic Framework Integrating Hyperchaotic Map and GRU

• URL: http://arxiv.org/abs/2510.12084v1
• Date: Tue, 14 Oct 2025 02:48:07 GMT
• Title: Elevating Medical Image Security: A Cryptographic Framework Integrating Hyperchaotic Map and GRU
• Authors: Weixuan Li, Guang Yu, Quanjun Li, Junhua Zhou, Jiajun Chen, Yihang Dong, Mengqian Wang, Zimeng Li, Changwei Gong, Lin Tang, Xuhang Chen,
• Abstract summary: Chaotic systems play a key role in modern image encryption due to their sensitivity to initial conditions, ergodicity, and complex dynamics.<n>This paper presents Kun-IE, a novel encryption framework designed to address these issues.<n>The framework features two key contributions: the development of the 2D Sin-Cos Pi Hyperchaotic Map, and the introduction of Kun-SCAN, a novel permutation strategy.
• Score: 14.484738921223352
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Chaotic systems play a key role in modern image encryption due to their sensitivity to initial conditions, ergodicity, and complex dynamics. However, many existing chaos-based encryption methods suffer from vulnerabilities, such as inadequate permutation and diffusion, and suboptimal pseudorandom properties. This paper presents Kun-IE, a novel encryption framework designed to address these issues. The framework features two key contributions: the development of the 2D Sin-Cos Pi Hyperchaotic Map (2D-SCPHM), which offers a broader chaotic range and superior pseudorandom sequence generation, and the introduction of Kun-SCAN, a novel permutation strategy that significantly reduces pixel correlations, enhancing resistance to statistical attacks. Kun-IE is flexible and supports encryption for images of any size. Experimental results and security analyses demonstrate its robustness against various cryptanalytic attacks, making it a strong solution for secure image communication. The code is available at this \href{https://github.com/QuincyQAQ/Elevating-Medical-Image-Security-A-Cryptographic-Framework-Integrating- Hyperchaotic-Map-and-GRU}{link}.

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