Enhancing Data Security and Privacy through Blockchain and Machine Learning

Abstract

Blockchain and Machine Learning (BML) are two of the most rapidly advancing technologies that are revolutionizing various industries worldwide. Blockchain is a widely known decentralized, immutable technology that provides a transparent, safe method of exchanging and storing data. In contrast, Machine Learning presents organizations with predictive analysis and automated decision-making abilities, enabling them to derive valuable insights from data. This study looks at how blockchain technology and machine learning are combining to try to improve data security and privacy. We have proposed a novel framework with the required components which integrates blockchain and machine learning. We have compared our proposed framework with ACO and SVM implemented frameworks with accuracy metric. Our system gave higher accuracy than former. Later we have provided discussion which encompasses the advantages, obstacles, and future implications of this integration, with a particular emphasis on its applications within the healthcare and financial industries. © 2024 IEEE.