A novel blockchain and fractional DCT based image storage and retrieval framework

Abstract

Securing medical images are a challenging task for researchers as they are prone to cyber- attacks. A potential solution to this problem can be blockchain, which provide secure and unchangeable storage. Fractional Discrete Cosine Transform (frDCT) has the capability to minimizes the amount of data necessary for expressing an image in a secure way. This paper presents a novel framework for compressing as well as securely storing and retrieving medical images by extraction of feature maps from medical images by frDCT, followed by encoding and storing the feature map on decentralized cloud and linking them on blockchain using fractional angle α. The proposed framework provides numerous benefits such as improved data sharing and collaboration, enhanced security, compression as well as efficient retrieval and processing of medical image data which in turn decreases the computational energy requirement providing sustainability. The performance of proposed framework has been evaluated by employing image quality metric such as MSE, PSNR, SSIM and multi-SSIM by comparing it with correct and incorrect α values on six different values of frDCT parameter α.