Blockchain-Watermarking scheme based K-Means for Medical Image

In recent years, there has been substantial growth in multimedia and visual data management. This increase in data volume presents several challenges, notably protecting multimedia content from tampering or manipulation. Images, as a prevalent form of multimedia content, often require protective techniques such as watermarking and blockchain, especially in medical contexts. Addressing challenges like watermark size and manipulations without third parties in multimedia data, including medical images, is crucial. This paper proposes a medical image protection scheme using a combination of watermark and blockchain techniques based on the k-means algorithm. This scheme utilizes k-means to compress the watermark image into an actual binary image, which is then embedded into the medical image using the least significant bit (LSB) technique, and then stored on the blockchain network. also, employing a bitwise XOR operation is applied to detect any manipulations by comparing it with the originally embedded binary image. The technique's efficacy is evaluated using the Peak Signal-to-Noise Ratio (PSNR) and subjected to various attacks, including different types of noise. Experimental and analytical results demonstrate that the proposed scheme effectively detects image manipulations and reduces the watermark size, enhancing security for medical images without third parties.