A Privacy and Integrity Protected Framework for Secure Telemedicine Applications

Telemedicine enhances remote healthcare by enabling timely, cost-effective diagnosis and treatment, while ensuring medical data security and integrity is essential. Traditional security methods, including AES and RSA encryption, DWT-based watermarking, and LSB steganography, provide protection but suffer from low robustness, vulnerability to attacks, and limited embedding capacity. To address these challenges, a Privacy and Integrity-Protected Framework is proposed by integrating Haar and Contourlet Transform, Spread Spectrum Steganography, and XOR Encryption. The Haar and Contourlet Transform enhance multi-resolution security for robust medical image embedding, while Spread Spectrum Steganography improves resistance to compression and noise, ensuring high imperceptibility. XOR Encryption provides fast and lightweight confidentiality, making it suitable for real-time telemedicine applications. Performance evaluation using PSNR, MSE, SSIM, and Embedding Capacity for CT and MRI images demonstrates superior robustness and imperceptibility. The proposed framework is evaluated on CT, MRI, and X-ray images, the proposed framework achieves outstanding visual quality with a PSNR of 53.68 dB, reduced MSE of 0.321, and an SSIM of 0.99. Comparative analysis highlights its superiority over traditional methods, ensuring enhanced security and efficiency for telemedicine applications.