Performance Enhancement of Blockchain Systems using AI based Consensus Mechanism

Blockchain is one of the trending technologies quite popular in the 21st century. It is the brain behind the widely known and used Bitcoin networks that is implemented on a simple mechanism of a shared, immutable, and distributed network. It is ideal if the information that needs to be fetched is immediate, sharable, and completely transparent and is stored on an immutable ledger that can be accessed by only permissioned network members. It facilitates the process of recording transactions and tracking assets in a business network. A Blockchain network can do much important work like tracking orders, payments, accounts, productions, and much more. The details of the transaction can be seen from end to end, giving greater confidence. One of the properties of the Blockchain network is that it is decentralized. So, the details of the Blockchain network are substantiated by a consensus algorithm. There are some traditional consensus algorithms that are widely used, including algorithms such as PoW (Proof of Work ) and PoS (Proof of Stake). They are a matter of concern due to their demerits of being computationally expensive and moving of system towards monopoly. Though there have been some optimizations on PoW and PoS, the problem still prevails. Especially the biggest challenge the Blockchain systems face is scalability. In this paper, a solution to the above problem is discussed by providing an algorithm based on Artificial Intelligence (Al) technology while reducing the demerits of the system. The main purpose Blockchain network serve is set up to generate data about the miners in order to train the machine learning model like Random Forest, KNN (K Nearest Neighbor), and Logistic Regression. The machine learning model gave outstanding results with improved efficiency and improved scalability.