An efficient medical image encryption using hybrid DNA computing and chaos in transform domain

Area of Science:

• Computer Science
• Information Security
• Medical Imaging

Background:

• Digital electronic health records (EHRs) face significant security risks during transmission over open networks.
• Encryption is a critical technique for safeguarding sensitive medical data.
• Existing encryption methods may not adequately address the complex security challenges of modern digital healthcare.

Purpose of the Study:

• To develop and evaluate a robust encryption algorithm for securing digital medical images.
• To enhance the confidentiality and integrity of electronic health records (EHRs).
• To provide a strong defense against statistical and differential attacks on medical image data.

Main Methods:

• A novel encryption algorithm combining Integer Wavelet Transform (IWT), DNA computing, and chaos theory.
• A two-phase encryption process involving shuffling (block confusion, row/column pixel shuffling) and diffusion (bitwise circular shifting, DNA coding, DNA XOR operations).
• Experimental validation using 100 DICOM test images with 16-bit depth.

Main Results:

• Achieved high security metrics, including maximum entropy averaging 15.79.
• Demonstrated strong resistance to differential attacks with NPCR (Number of Pixels Change Rate) of 99.99% and UACI (Unified Average Changing Intensity) of 33.31%.
• Established a large keyspace of 10^140, indicating superior security compared to existing methods.

Conclusions:

• The proposed IWT-DNA-chaos based encryption algorithm offers a highly secure and effective solution for protecting digital medical images.
• The algorithm's performance surpasses various state-of-the-art techniques in terms of security and resistance to attacks.
• This approach provides a promising direction for securing sensitive electronic health records (EHRs) in digital healthcare environments.