article · Scientific Reports
A hybrid image encryption framework pairs a two-dimensional chaotic Baker map with XOR-based diffusion to secure medical imagery against digital threats. The approach uses chaotic permutation via pseudo-random sequences derived from the Baker map, alongside an XOR diffusion stage designed to raise pixel randomness and block attacks. Experimental testing demonstrates near-ideal randomness with an entropy score of 7.9897, alongside strong resistance to differential and statistical attacks evidenced by a number of changing pixel rate of 99.6521 percent and a unified average changing intensity of 31.306 percent. Adjacent pixels exhibit minimal correlation, whilst decrypted images preserve high reconstruction quality. When implemented on a Field Programmable Gate Array, the design maintains low hardware resource utilisation and supports real-time performance. This combination of efficiency and protection provides a viable solution for safeguarding data within Internet of Medical Things and Healthcare 4.0 systems.
Transmitting and storing sensitive medical records across modern healthcare networks creates serious data protection vulnerabilities. Traditional encryption tools often demand too much computing power for real-time or resource-limited hardware. Developing lightweight, chaos-based encryption that runs directly on hardware enables secure, instantaneous medical imaging transmission, helping protect patient confidentiality across interconnected clinics and remote care devices without compromising image clarity or operational speed.
This technology is targeted at Internet of Medical Things and Healthcare 4.0 architectures, where medical device manufacturers and healthcare technology providers require real-time data security. Because the design has been successfully implemented and validated on a Field Programmable Gate Array with low resource requirements, it sits at an applied, tested stage of development, ready for further integration into hardware-level security modules for connected diagnostic and imaging equipment.
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As the digital ecosystem evolves, the widespread generation, transmission, and storage of medical images expose sensitive healthcare data to significant security threats, necessitating robust and efficient encryption techniques. While several chaos-based encryption methods have been proposed, many suffer from limited key spaces and high computational complexity, making them unsuitable for real-time and resource-constrained environments. This paper presents a hybrid image encryption framework that integrates a two-dimensional Chaotic Baker Map (2D-CBM) with XOR-based diffusion to achieve both high security and computational efficiency. The proposed method performs chaotic permutation using a pseudo-random sequence derived from the Baker map, followed by an XOR-based diffusion process to enhance pixel randomness and resistance to attacks. Extensive experimental evaluation demonstrates that the proposed method achieves high entropy H = 7.9897, indicating near-ideal randomness, along with NPCR = 99.6521% and UACI = 31.306%, confirming strong resistance against differential and statistical attacks. In addition, the proposed framework ensures low correlation among adjacent pixels and maintains high reconstruction quality after decryption. Furthermore, the algorithm is efficiently implemented on a Field Programmable Gate Array (FPGA), demonstrating low resource utilization and suitability for real-time secure medical image processing. The proposed system is well-suited for deployment in Internet of Medical Things (IoMT) and Healthcare 4.0 environments, where both security and efficiency are critical.
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DOI: 10.1038/s41598-026-66018-x
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