A Light Weight Biomedical Image Encryption & Decryption Using SH-512 and 7D

Abstract

In the digital era, the secure transmission and
storage of sensitive biomedical images such as
MRI, CT scans, and X-rays have become
paramount due to their critical role in healthcare
and diagnosis. This project presents a robust
image encryption and decryption system that
leverages the power of SHA-512 (Secure Hash
Algorithm 512-bit) and a 7-Dimensional
Hyperchaotic System to ensure high-level
confidentiality, integrity, and robustness against
modern cryptographic attacks. The proposed
method begins by preprocessing the biomedical
image and converting it into a pixel matrix. The
SHA-512 hash function is applied to generate a
unique key based on the image content or user
input, which significantly enhances key sensitivity
and resists brute force attacks. Simultaneously, a
7D hyperchaotic system, known for its complex
nonlinear behavior and sensitivity to initial
conditions, is used to generate pseudo-random
sequences. These sequences are utilized for pixel
permutation (confusion) and intensity
modification (diffusion), two critical stages in
image encryption. The encryption process
combines hash-based scrambling, pixel-level
substitution, and chaotic key masking to generate
a ciphered image that is visually
incomprehensible and statistically unpredictable.
The decryption process follows the reverse steps
using the same keys, restoring the original image
with lossless quality. This hybrid approach
ensures several advantages: strong resistance
against differential attacks, histogram uniformity,
high key space complexity (> 2^512), and
minimal correlation between adjacent pixels. The
system is implemented as a web application using
HTML, CSS, Tailwind, JavaScript, and Vite, and
supports both light and dark themes for user
adaptability. Overall, this encryption framework
not only secures biomedical data transmission
over untrusted networks but also provides a
flexible, lightweight, and scalable solution
suitable for deployment in telemedicine, cloud
storage, and healthcare information systems.