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Area of Science:

  • Medical Imaging
  • Cryptography
  • Computer Science

Background:

  • Radiological images are crucial for healthcare but challenging to analyze, especially during pandemics.
  • Medical data transmission requires robust security, including confidentiality, integrity, and availability.
  • Chaos-based cryptography offers robust medical image encryption due to enhanced unpredictability.

Purpose of the Study:

  • To propose a modified, time-efficient encryption technique for 2D COVID-19 images.
  • To enhance the security and unpredictability of medical image encryption on low-precision devices.
  • To ensure data integrity and confidentiality during medical image transmission.

Main Methods:

  • A three-part encryption process involving a variable length gray level code for secret key generation.
  • Pixel shuffling using address codes derived from a logistic map.
  • Image diffusion using a second chaotic map to resist differential and statistical attacks.

Main Results:

  • The proposed algorithm was validated on visual and COVID-19 X-ray images.
  • Quantitative analysis confirmed negligible data loss between original and decrypted images.
  • Security parameters (correlation coefficient, NPCR, UACI, key sensitivity) demonstrated the method's strength.

Conclusions:

  • The modified chaotic encryption technique is effective and secure for COVID-19 images.
  • The method is time-efficient and suitable for low-precision devices.
  • It offers improved unpredictability and robust protection against attacks.