iProtector: Using biometric empowered key to encrypt the medical images with secure transmission through robust coverless steganography.

BACKGROUND AND OBJECTIVE: With the widespread adoption of smart electronic devices, medical images have become a core information carrier in clinical practice. These devices facilitate the seamless exchange of medical images through collaborative interconnection, thereby significantly enhancing both functionality and user experience. However, such sensitive image information is inherently vulnerable to risks such as theft, unauthorized access, and financial fraud during storage and transmission. METHOD: To address these challenges, we propose a medical image security technique, called iProtector, which combines encryption, robust coverless steganography, and biometric (voice)-based identity verification to meet the stringent security requirements of healthcare. Our method introduces three key innovations. First, a novel key is generated using biometric (voice) data, deep-learning-based image features, device-specific information, and a lightweight hash-based encryption algorithm for image encryption. Second, coverless steganography is used to enhance the security of data transmission. Third, an access control system based on voice-based identity verification is proposed to reduce the risks of theft and unauthorized access. RESULTS: Experimental results demonstrate that the proposed iProtector ensures robust data integrity and security while reducing the risks of theft and unauthorized access, thereby satisfying the security and authenticity requirements of healthcare data. To the best of our knowledge, we are the first to explore a reliable integration of biometrics, encryption, and coverless steganography with an access control system for healthcare applications. CONCLUSION: These features make iProtector particularly suitable for secure healthcare applications.