Secure Medical Image Transmission via CNN-Derived Keys and Chaotic DNA Encoding - Bentouila, Sara; Faraoun, Kamel Mohamed (IAES Indonesian Section, 2025)
This paper presents a secure and efficient hybrid encryption framework designed for medical image protection. The method combines a fine-tuned MobileNetV3 network for content-adaptive key generation with the nonlinear dynamics of a Lu chaotic system and a DNA-based Cipher Feedback (CFB) diffusion stage. The proposed approach eliminates the arbitrary selection of chaotic maps commonly found in existing methods by dynamically adapting to image content. Experimental tests conducted on brain MRI images demonstrate strong security and robustness, achieving an entropy of 7.9998, NPCR of 99.58%, UACI of 29.93%, PSNR of 7.43 dB, and an average encryption time of 0.24 s. These results confirm excellent randomness, high key sensitivity, and real-time processing capability. The proposed model outperforms recent chaotic and hybrid schemes, making it suitable for secure medical image transmission and telemedicine applications.