Robust Digital Medical Image Watermarking and Encryption Algorithms Using Blockchain over DWT Edge Coefficient
Paresh Rawat, Piyush Kumar Shukla · Auerbach Publications eBooks · 2021
Watermarking methods are popular in the protection and authentication of digital images. In the case of medical imaging data, the watermark must be robust and invisible to the human eye. Yet wavelet-based watermark embedding methods are now very common and now can be easily decoded by hackers. The existing watermarking methods have only focused on the perceptual quality of watermarked images. To date, there has been little exploration of the process of generation or of the memory storage of the watermark images. Accordingly, this chapter is designed for a new methodology to generate and decode the digital watermark. A robust algorithm as a combination of the watermarking and Blockchain-based hash functions is designed. The Blockchain in watermarking algorithm is used to safely store the watermark information. A discrete wavelets transform (DWT)-based watermarking method is evaluated in this chapter. An encryption method unsighted hash-256 function is used to generate hash value based on the local image features. The watermark rule must be simple but also robust. This chapter aims to design a watermarking method using DWT and edge detection coefficient values and the robust block chain technique. The edge detection using wavelet adds the invisibility to watermark. This chapter has illustrated the basic medical image authenticating methods using different combinations of the DWT- and SVD-based embedding rules for a fixed block of chain. A generated Blockchain is shuffled and encrypted using the SHA-256 algorithm. The proposed method in this chapter adopts the energy efficient wavelet coefficient for minimizing the spatial localities for better invisibility. In addition, the watermark color space is adopted using an energy-efficient manner, to embed the watermark. In the proposed method, the host image is decomposed to N-level DWT coefficients then the SVD coefficient are used for embedding the watermark to image. The performance is tested using the various watermark attacks. The performance is compared based on the extraction quality and parametric studies.