Medical image encryption using adaptive key generation and hybrid chaotic maps with multi-round diffusion
itha HG Yash, Anita S. Kini · 2026
With the growing use of telemedicine and Internet of Medical Things (IoMT), secure transfer of medical images is now a matter of utmost concern. Although traditional encryption techniques such as advanced encryption standard and RSA (Rivest—Shamir—Adleman) provide security, they tend to be computationally expensive and not fit for real-time, light-weight healthcare purposes. In contrast, this paper introduces a new and effective image encryption method combining hybrid chaotic maps and adaptive key generation with multiple-round feedback diffusion. The random key stream is dynamically produced from the statistical properties of every input image, providing data-dependent encryption with high sensitivity. Pixel permutation and a two-stage feedback XOR diffusion process are powered by a combination of Logistic and Tent maps, improving confusion and diffusion. Experimental results on different medical images (CT, MRI, X-ray, Ultrasound) demonstrate robust cryptographic performance with entropy values approaching 8, NPCR above 99.6%, and UACI approximately 50%. The decrypted images are completely restored (MSE = 0, PSNR = ∞), and key sensitivity analysis verifies strong resistance against brute-force attacks. These characteristics render the proposed scheme a viable and lightweight solution for real-time protection of medical images in IoT-based healthcare environments