A Blockchain-Enabled Adaptive Learning Model for Secure and Scalable Data Sharing

The blockchain skillset is one of the most emerging skill sets that brings the world into the hands of the self. The number of industrial applications depends on this new technology just because of its decentralized, transparent, and secure nature. This enables a new way for the next generation of computing environments like cloud computing and edge computing. By keeping this in mind, this work develops a new disruptive method using adaptive learning model to address the security issues in a data sharing environment with decentralized access control. The developed framework has been executed and tested utilizing Python, and the results have been presented. A performance study comparison between the existing RSA algorithm, AES algorithm, and the proposed algorithm (ALM) has been done, and the various parameters taken for the study and their values are presented in this paper. Results obtained show that the algorithm presented is proven to be efficient in terms of security, scalability and time. © Mohanambal. B. et al.