In the digital era of healthcare care, medical images play a crucial role in diagnosis and patient monitoring. Due to their sensitive and personal nature, a robust encryption system is required - one that protects data confidentiality without compromising visual fidelity. This study proposes a medical image encryption framework based on the Lorenz chaotic algorithm, integrated with Discrete Wavelet Transform (DWT) and digital signature embedding to ensure data integrity, authenticity, and security.
The system generates Visually Meaningful Encrypted Images (VMEI), enabling the encrypted images to retain a recognizable structure. A role-based architecture is implemented that divides users into administrators (for data input) and doctors (for validation and decryption), while employing a two-level authentication mechanism through patient identity and registered digital signature verification.
Experimental results demonstrate that the system effectively maintains high visual quality and data recovery accuracy. Under an optimal configuration using a 1024 x 1024 secret image, 4096 x 4096 carrier, and 256 x 256 signature, with alpha values of 0.28 for the secret and 0.07 for the signature, and a Lorenz initial condition of (0.2, 0.8, 1.5), the system achieved a PSNR greater than 30 dB for the secret image decrypted, with low BER values. This indicates reliable data embedding and reconstruction without significant visual degradation. In addition, the system demonstrated resilience to image rotation, which is crucial for the transmission of medical data in the real world.
Compared to previous approaches, this system not only achieves competitive visual performance but also introduces an integrated and role-aware digital signature authentication mechanism. The combination of chaotic cryptography, frequency domain transformation, digital signature embedding, and role-based access control makes this system well suited for secure applications in digital healthcare environments requiring multilevel validation.
This encryption framework provides a significant contribution to the field of medical image security by ensuring high visual quality, strong access control, and securely authenticated data reconstruction within healthcare ecosystems.
Keywords: image encryption, Lorenz algorithm, DWT, digital signature, PSNR,
BER, visually meaningful image