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QMedShield: A Novel Quantum Chaos-based Image Encryption Scheme for Secure Medical Image Storage in the Cloud

Arun Amaithi Rajan, Vetriselvi V

TL;DR

QMedShield tackles the security of medical images stored in cloud environments by integrating quantum-chaos dynamics with bit-plane scrambling and DNA encoding. The method combines diffusion via a 3D quantum logistic map and Henon/Hybrid chaotic maps with quantum Hadamard-CNOT operations and DNA-based confusion, producing cipher images with strong statistical and differential resistance. Extensive experiments on BMRI, CXR, and LCT datasets demonstrate high key sensitivity, near-uniform histograms and entropy, and robust resistance to known-, chosen-, and differential-attacks, outperforming several prior schemes in key metrics. The work highlights the feasibility and practicality of quantum-chaos–based encryption for safeguarding sensitive healthcare data in the cloud, and points to future enhancements using higher-dimensional quantum maps and expanded scrambling strategies.

Abstract

In the age of digital technology, medical images play a crucial role in the healthcare industry which aids surgeons in making precise decisions and reducing the diagnosis time. However, the storage of large amounts of these images in third-party cloud services raises privacy and security concerns. There are a lot of classical security mechanisms to protect them. Although, the advent of quantum computing entails the development of quantum-based encryption models for healthcare. Hence, we introduce a novel quantum chaos-based encryption scheme for medical images in this article. The model comprises bit-plane scrambling, quantum logistic map, quantum operations in the diffusion phase and hybrid chaotic map, DNA encoding, and computations in the confusion phase to transform the plain medical image into a cipher medical image. The proposed scheme has been evaluated using multiple statistical measures and validated against more attacks such as differential attacks with three different medical datasets. Hence the introduced encryption model has proved to be attack-resistant and robust than other existing image encryption schemes, ensuring the secure storage of medical images in cloud environments.

QMedShield: A Novel Quantum Chaos-based Image Encryption Scheme for Secure Medical Image Storage in the Cloud

TL;DR

QMedShield tackles the security of medical images stored in cloud environments by integrating quantum-chaos dynamics with bit-plane scrambling and DNA encoding. The method combines diffusion via a 3D quantum logistic map and Henon/Hybrid chaotic maps with quantum Hadamard-CNOT operations and DNA-based confusion, producing cipher images with strong statistical and differential resistance. Extensive experiments on BMRI, CXR, and LCT datasets demonstrate high key sensitivity, near-uniform histograms and entropy, and robust resistance to known-, chosen-, and differential-attacks, outperforming several prior schemes in key metrics. The work highlights the feasibility and practicality of quantum-chaos–based encryption for safeguarding sensitive healthcare data in the cloud, and points to future enhancements using higher-dimensional quantum maps and expanded scrambling strategies.

Abstract

In the age of digital technology, medical images play a crucial role in the healthcare industry which aids surgeons in making precise decisions and reducing the diagnosis time. However, the storage of large amounts of these images in third-party cloud services raises privacy and security concerns. There are a lot of classical security mechanisms to protect them. Although, the advent of quantum computing entails the development of quantum-based encryption models for healthcare. Hence, we introduce a novel quantum chaos-based encryption scheme for medical images in this article. The model comprises bit-plane scrambling, quantum logistic map, quantum operations in the diffusion phase and hybrid chaotic map, DNA encoding, and computations in the confusion phase to transform the plain medical image into a cipher medical image. The proposed scheme has been evaluated using multiple statistical measures and validated against more attacks such as differential attacks with three different medical datasets. Hence the introduced encryption model has proved to be attack-resistant and robust than other existing image encryption schemes, ensuring the secure storage of medical images in cloud environments.
Paper Structure (28 sections, 26 equations, 17 figures, 9 tables)

This paper contains 28 sections, 26 equations, 17 figures, 9 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. Preliminaries
  4. Bit Plane Scrambling
  5. Chaotic Maps
  6. Henon Chaotic Map
  7. Hybrid Chaotic Map
  8. 3D Quantum Logistic Chaotic Map
  9. Quantum Operations
  10. Hadamard Gate
  11. CNOT Gate
  12. DNA encoding
  13. Proposed Encryption Model
  14. Algorithm of QMedShield
  15. Experimental Results and Analysis
  16. ...and 13 more sections

Figures (17)

  • Figure 1: Secure Cloud Storage
  • Figure 2: Overall Block Diagram
  • Figure 3: Bit plane Scrambling
  • Figure 4: Bifurcation diagram of Henon Map: $\beta$=0.3
  • Figure 5: Hybrid Logistic-Sin Map Bifurcation diagram
  • ...and 12 more figures