Medical Image Data Provenance for Medical Cyber-Physical System
Vijay Kumar Kolin Paul
Continuous advancements in medical technology have led to the creation of
affordable mobile imaging devices suitable for telemedicine and remote
monitoring. However, the rapid examination of large populations poses
challenges, including the risk of fraudulent practices by healthcare
professionals and social workers exchanging unverified images via mobile
applications. To mitigate these risks, this study proposes using watermarking
techniques to embed a device fingerprint (DFP) into captured images, ensuring
data provenance. The DFP, representing the unique attributes of the capturing
device and raw image, is embedded into raw images before storage, thus enabling
verification of image authenticity and source. Moreover, a robust remote
validation method is introduced to authenticate images, enhancing the integrity
of medical image data in interconnected healthcare systems. Through a case
study on mobile fundus imaging, the effectiveness of the proposed framework is
evaluated in terms of computational efficiency, image quality, security, and
trustworthiness. This approach is suitable for a range of applications,
including telemedicine, the Internet of Medical Things (IoMT), eHealth, and
Medical Cyber-Physical Systems (MCPS) applications, providing a reliable means
to maintain data provenance in diagnostic settings utilizing medical images or
videos.