Efficient hardware realization of 2D-chaotic Baker map using FPGA for secure image encryption

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.