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Medical image encryption using fractional discrete cosine transform with chaotic function.

Sumit Kumar1, Bhaskar Panna2, Rajib Kumar Jha2

  • 1Department of Electrical Engineering, Indian Institute of Technology Patna, Bihta, India. sumitphd13@gmail.com.

Medical & Biological Engineering & Computing
|September 13, 2019
PubMed
Summary

This study introduces a novel method for securing medical images using chaotic maps and fractional discrete cosine transform (FrDCT). The proposed encryption scheme enhances medical data safety against fraud and unauthorized access.

Keywords:
ChaoticDecryptionEncryptionFractional cosine transformKey sensitivityKey spaceMedical image

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Area of Science:

  • Medical Imaging
  • Cryptography
  • Digital Signal Processing

Background:

  • Increasing internet usage necessitates robust security for large medical datasets.
  • Medical image data requires protection against forgery and fraud for accurate diagnosis.
  • Existing methods face challenges in securely transmitting and reusing medical images.

Purpose of the Study:

  • To propose a new scheme for securing medical data/images.
  • To enhance the safety and integrity of medical image information.
  • To explore the application of chaotic maps on FrDCT coefficients for image encryption.

Main Methods:

  • Applying fractional discrete cosine transform (FrDCT) to medical images.
  • Utilizing a chaotic map on the FrDCT coefficients for encryption.
  • Comparing the proposed FrDCT method with the fractional Fourier transform (FRFT).

Main Results:

  • The proposed algorithm demonstrates high security and key sensitivity for various medical images.
  • Experiments confirm the effectiveness and advantages of FrDCT over FRFT for image encryption.
  • The method shows superior performance compared to existing state-of-the-art techniques.

Conclusions:

  • The developed scheme effectively secures medical images against unauthorized access and manipulation.
  • The use of chaotic maps with FrDCT offers a promising approach for medical data protection.
  • This work provides a foundation for further research in secure medical image processing.