Personal health records and electronic health records are considered as the most sensitive information in the healthcare domain. Several solutions have been provided for implementing the digital health system using blockchain, but there are several challenges, such as secure access control and privacy is one of the prominent issues. Hence, we propose a novel framework and implemented an attribute-based access control system using blockchain. Moreover, we have also integrated artificial intelligence (AI) based approach to identify the behavior and activity for security reasons. The current methods only focus on the related clinical records received from a medical diagnosis. Moreover, existing methods are too inflexible to resourcefully sustenance metadata changes. A secure patient data access framework is proposed in this research, integrating blockchain, trust chain, and blockchain methods to overcome these problems in the literature for sharing and accessing digital healthcare data. We have used a neural network and classifier to categorize the user access to our proposed system. Our proposed scheme provides an intelligent and secure blockchain-based access control system in the digital healthcare system. Experimental results surpass the existing solutions by collecting attributes such as the number of transactions, number of nodes, transaction delay, block creation, and signature verification time.
Funding Statement: This research was supported by Taif University Researchers Supporting Project number (TURSP-2020/98), Taif University, Taif, Saudi Arabia.
