Elevating Medical Image Security: A Cryptographic Framework Integrating Hyperchaotic Map and GRU
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}.
Cite
@article{arxiv.2510.12084,
title = {Elevating Medical Image Security: A Cryptographic Framework Integrating Hyperchaotic Map and GRU},
author = {Weixuan Li and Guang Yu and Quanjun Li and Junhua Zhou and Jiajun Chen and Yihang Dong and Mengqian Wang and Zimeng Li and Changwei Gong and Lin Tang and Xuhang Chen},
journal= {arXiv preprint arXiv:2510.12084},
year = {2025}
}
Comments
Accepted By BIBM 2025