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A new medical image encryption using modular integrated logistic exponential map and multi-level Q-Sequence matrix.

Abdelmajid H Mansour1, Sherihan Aboelenin2, Mohamed Meselhy Eltoukhy2

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This study introduces a novel encryption algorithm for medical images, enhancing data security and privacy. The method uses a Modified Improved Logistic Exponential (MILE) chaotic map and multi-level Fibonacci Q-matrix for robust protection in healthcare.

Keywords:
ChaoticColor medical imagesEncrypting imagesEncryptionExponential mapFibonacciLogistic mapMILEScrambled image blocks

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Area of Science:

  • Medical Imaging Security
  • Cryptography
  • Information Technology in Healthcare

Background:

  • Confidentiality of medical images is critical for patient privacy and data integrity in healthcare.
  • Existing encryption methods may face limitations in security, efficiency, or resilience against advanced attacks.

Purpose of the Study:

  • To develop an innovative and efficient encryption algorithm for both grayscale and color medical images.
  • To enhance the security, randomness, and resilience of medical image data during storage and transmission.

Main Methods:

  • The proposed algorithm combines a Modified Improved Logistic Exponential (MILE) chaotic map with a multi-level Fibonacci Q-matrix.
  • It employs key-dependent parameter extraction, chaotic sequence generation for permutation and XOR-based diffusion, and multi-level Q-matrix transformations.
  • The method addresses limitations of 1D chaotic systems for improved unpredictability.

Main Results:

  • The encryption scheme demonstrated strong performance with high NPCR (99.63%) and UACI (33.47%) values.
  • Entropy values approached the ideal 7.999, indicating excellent randomness and resistance to statistical attacks.
  • The algorithm is computationally efficient, encrypting a 256x256 image in 0.42 seconds.

Conclusions:

  • The proposed encryption algorithm offers robust protection for sensitive medical data.
  • Its efficiency and strong security features make it suitable for real-time applications and telemedicine.
  • The method outperforms several existing medical image encryption techniques.