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Enhanced security for medical images using a new 5D hyper chaotic map and deep learning based segmentation.

S Subathra1, V Thanikaiselvan2

  • 1School of Electronics Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India, 632014.

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Summary

This study introduces a novel 5D hyperchaotic system and U-Net architecture for secure medical image encryption, enhancing patient data privacy. The method ensures robust security against attacks with high encryption efficiency.

Keywords:
Critical region segmentationDynamic DNA encodingHyper-chaotic mapImage encryptionU-NetZig-zag scrambling

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Area of Science:

  • Computer Science
  • Information Security
  • Medical Imaging

Background:

  • Medical image encryption is crucial for protecting sensitive patient data and ensuring privacy in digital healthcare systems.
  • Existing encryption methods may not adequately address the unique security challenges posed by medical images.

Purpose of the Study:

  • To propose a new secure medical image encryption algorithm using a 5D hyperchaotic system and a U-Net architecture.
  • To enhance the confidentiality and integrity of medical data against various security threats.

Main Methods:

  • A novel 5D hyperchaotic system is combined with a customized U-Net for medical image segmentation.
  • Image statistics are used as initial conditions for generating random sequences.
  • Zig-zag scrambling, permutation, dynamic DNA flip, and dynamic DNA XOR diffusion stages are employed.

Main Results:

  • The proposed algorithm achieves a large key space (2^500) and high encryption efficiency (approx. 2.93s per image).
  • Statistical tests (NIST SP800-22, Lyapunov exponent, entropy, Chi-square) confirm the randomness and security of the system.
  • High NPCR (99.61%) and UACI (33.49%) values indicate strong diffusion and confusion.

Conclusions:

  • The proposed medical image encryption method offers secure and reliable protection for sensitive patient data.
  • The combination of a 5D hyperchaotic system and U-Net architecture provides a robust solution for medical image security.