An Optimized and Secured Image Watermarking and Its Dual Authentication for Internet of Medical Things

The data used in the medical field have significantly expanded in recent years, especially after the pandemic. This type of data is shared over the cloud for verification and diagnosis. The patients and researchers share sensitive information and images of the medical field, so this information must be secured during transmission. Henon map is used to enhance the security of proposed work. The Schur decomposition, along with redundant discrete wavelet transform and randomized singular value decomposition, is used for embedding. The first watermark, i.e., the Aadhar card of patient, is modified using media access control (MAC) address. The second watermark image is created by fusing two images, a magnetic resonance imaging and a computerized tomography scan, using dual tree complex wavelet transform (DT-CWT). White shark optimization is used to get the optimum scaling factor. A secured hash algorithm is used for the authentication of the identity of the patient and MAC address. The average percentage improvement in imperceptibility is 25.98%, and in robustness is 14.01%.