Lightweight semantic compression visual cryptography for secure medical image transmission in IoT systems

Area of Science:

• Computer Science
• Information Security
• Medical Imaging

Background:

• Secure transmission of sensitive medical images is critical in IoT healthcare.
• Resource-constrained IoT devices pose challenges for traditional security methods.
• Maintaining data confidentiality, integrity, and authenticity is paramount.

Purpose of the Study:

• To propose a novel lightweight visual cryptography framework for secure medical image transmission.
• To address computational and storage limitations of IoT devices.
• To ensure robust security and high-quality reconstruction.

Main Methods:

• Developed a framework using semantic compression and visual cryptography.
• Encoded grayscale medical images into multiple visual shares.
• Employed modular arithmetic-based lightweight encryption techniques.

Main Results:

• Achieved high-quality image reconstruction with PSNR > 34 dB and SSIM ≈ 0.99.
• Demonstrated security against tampering and eavesdropping.
• Framework balances computational efficiency, reconstruction quality, and security.

Conclusions:

• The proposed framework offers a robust solution for secure medical image transmission in IoT environments.
• It effectively mitigates security risks while respecting device constraints.
• Shows strong potential for enhancing security in healthcare IoT applications.