A simple embed over encryption scheme for DICOM images using Bülban Map.

Area of Science:

• Medical Imaging
• Cybersecurity
• Data Protection

Background:

• Pandemics significantly increase medical image data, creating vulnerabilities for sensitive patient information.
• Medical images are targets for hackers seeking patient data and health details.
• Existing security measures may not adequately protect the integrity and confidentiality of medical images.

Purpose of the Study:

• To propose and evaluate a new algorithm for securing medical images.
• To embed patient identification numbers and encrypt medical images to protect patient identity and medical conditions.
• To enhance the security of medical image databases against unauthorized access.

Main Methods:

• Developed a novel algorithm involving secret embedding of patient identification numbers.
• Implemented a single-stage confusion and two-stage diffusion encryption process.
• Utilized the Bülban map for key generation, 5/3 transformation in the transform domain, and spatial domain pixel alteration for diffusion.
• Tested the algorithm on over 30 Digital Imaging and Communications in Medicine (DICOM) images from the Open Science Framework (OSF).

Main Results:

• The algorithm demonstrated resistance to statistical attacks.
• Achieved a Peak Signal-to-Noise Ratio (PSNR) of 7.084 dB and entropy of 15.9815 bits for the cipher image.
• Reported low correlation coefficients (0.0275, -0.0027, 0.018) in horizontal, vertical, and diagonal directions.
• Exhibited high key sensitivity with a keyspace of 2^((M-1)×N×16).

Conclusions:

• The proposed algorithm is effective for embedding patient information and encrypting medical images.
• The security metrics confirm the algorithm's robustness against potential threats.
• This approach provides a viable solution for safeguarding medical image data in pandemic scenarios.