Machine Learning-based Adaptive Access Control Mechanism for Private Blockchain Storage.

The focus of our paper is to explore the concept of blockchain, which is a digitalized, shared, and decentralized network where every transaction can be viewed by all users with access to the blockchain. Our main objective is to develop an access control mechanism for our private blockchain, which is implemented using Ethereum. This mechanism will use a machine learning-based security layer to regulate user access, allowing or denying access based on predetermined rules. Our ultimate goal is to create a mechanism that is highly secure, maintains data confidentiality, and improves user authenticity. To achieve the objectives, we construct a client-side model with an appealing graphical user interface that enables users to take advantage of the unique functionalities offered by the private blockchain. This paper will help to determine the most effective strategies for building a secure and reliable access control mechanism for blockchain networks.