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This research aims to enhance medical image security through a dual-encryption framework that combines quantum and DNA techniques.

May 7, 2026Open Access

Enhancing medical image security with quantum DNA dual encryption

SISaba InamFatima Jinnah Women University SKShamsa KanwalFatima Jinnah Women University RARehana AmirFatima Jinnah Women University

Key Points

This research aims to enhance medical image security through a dual-encryption framework that combines quantum and DNA techniques.
Utilized chaos-based quantum encryption with a DNA codec and Quantum Fibonacci Transform (QFBT).
Converted standard color images to quantum data via Generalized Quantum Image Representation (GQIR).
Applied quantum XOR functions using transformed images as key matrices.
Mean NPCR for RGB channels was 99.63%, indicating effective pixel change.
Achieved UACI of 33.43%, reflecting intensity changes in the image.
Mean information entropy approximated at 7.9992, showing high randomness in encrypted images.

Abstract

Ensuring patient secrecy and maintaining data integrity are critical in healthcare information security. With increasing demands for stronger protection in the management and storage of medical images, this study introduces an innovative framework utilizing chaos-based quantum encryption for enhanced security. This approach combines a DNA codec with the QFBT (Quantum Fibonacci Transform), creating a unique dual-encryption method for quantum color images. The process begins with converting a standard color image to quantum data through GQIR (Generalized Quantum Image Representation) technique. A DNA codec then encodes and decodes the pixel color data of the quantum image, achieving pixel-level diffusion. Finally, the QFBT is applied to scramble the image's spatial data. The resulting transformed image is then used as the key matrix in quantum XOR functions. Findings from the experiment indicate that both the correlation and peak value of the encrypted image histograms show strong similarity. The mean NPCR (Normalized Pixel Change Rate) for the RGB channels is 99.63%, while UACI (Uniform Average Change Intensity) is 33.43%. Additionally, the mean information entropy is approximately 7.9992. These findings demonstrate the effectiveness of QDIES in providing robust security for medical image data.

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