International Journal of Scientific Research and Engineering Development

The rapid proliferation of digital healthcare and telemedicine has significantly increased the use of medicalimaging for diagnosis and patient monitoring. Chest X-ray images are critical for detecting lung infections, fractures, tumors, and other life-threatening diseases. However, their transmission and storage over networks expose sensitive patient information to unauthorized access, cyberattacks, and data tampering. This paper presents a secure medical image protection framework — "Larger Chunk-Adaptive Integrated AES and RSA for Chest X-Ray Image Encryption" — that combines AES-256 symmetric encryption with RSA-2048 asymmetric key encapsulation. Images are first preprocessed using an Adaptive Median Filter (AMF) to remove noise and improve quality, then divided into larger adaptive chunks for optimized processing. Performance is evaluated using Encryption Time, Decryption Time, MSE, PSNR, SSIM, Correlation Coefficient, Entropy, NPCR, and UACI. Experimental results confirm improved encryption efficiency, reduced processing time, enhanced security, and strong resistance against statistical and brute-force attacks compared to traditional methods.

P.Logaiyan, J.Yokeshkumar,"Medical Image Security Framework using X-Ray Image Encryption: Larger Chunk-Adaptive Integrated AES and RSA for Chest X-Ray Image Encryption" International Journal of Scientific Research and Engineering Development, V9(3): Page(2151-2157) May-June 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.