A DWT-Based Model with CNN-based Decision Fusion Strategy for Medical Image Encryption Scheme for Healthcare Network

Abstract

Telemedicine and digital health are expanding rapidly, increasing the demand for secure and precise transmission of medical images. This study introduces an innovative hybrid model that combines DWT, CNN, and encryption techniques for safe image processing. The Proposed DWR-CNN model secures image embedding, hybrid encryption, and deep learning classification techniques. Medical images are concealed within a reference image using methods such as SVD to maintain their confidentiality while remaining unaltered. The image is subsequently transformed using DWT to enhance its resilience against attacks. A blend of AES and ECC protects the image transfer. VGG16 and YOLOv8 are to extract features and identify errors. The DWT-CNN model encourages precision and robust safety in evaluations using medical imaging datasets.