An integrated biomedical images security approach to secure healthcare system

An integrated biomedical images security approach to secure healthcare system

연구 분야: Infrastructure

학회: Neural Computing and Applications

Smart healthcare holds immense potential to revolutionize the healthcare industry, promoting patient-centric care, preventive medicine, and improved health outcomes. By harnessing the power of advanced technologies and data-driven solutions, healthcare providers can deliver more efficient, accessible, and personalized healthcare services, ultimately transforming the approach and experience of healthcare. Biomedical images have now become the new support for better diagnosis in the medical field. In the area of image security, perceptual hashing provides a powerful approach to enhancing the security of medical images by creating compact and unique representations of their visual content. This paper proposes a framework for smart healthcare where biomedical images are secured with perceptual hashing. In this framework, an authentication module is also deployed to verify the identity of smart users allowed to access the biomedical images over the edge or cloud layers. The performance analysis of the hashing module is evaluated using the structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), bit error rate (BER), and Hausdorff distance. Additionally, the performance analysis of the authentication module is evaluated in terms of a system accuracy of 89% and a probability of identification of 0.45 to establish authentication.