Blockchain-Integrated Machine Learning for Autonomous IoT Networks: A Paradigm Shift in Data Security

Abstract

With the introduction of the idea of the IoT (the Internet of Things), new opportunities and the issues that come along with it in the area of data safety are created. The greater the number of devices connected to the Internet of Things network, the more complex and bulky the field of securing data becomes. The Blockchain and Machine Learning (ML) technology can provide a solution to that end in order to eliminate such challenges. Blockchain offers privacy, transparency and scalable features through which data integrity is improved, and the ML brain is a solution to facilitate autonomous decision and detecting anomalies inside the IoT network. In this paper, the author explains how Blockchain and ML may be used to create a secure and stable IoT ecosystem. It talks about how the integration can maximize data security and the optimum resources and scalability of independent operations of the networks IoT. The study also speaks about the possible benefits, difficulties and the future consequences of such paradigm shift on the security of the data. Through its critical investigation, the following paper is going to provide an outline of future studies and potential application of Machine Learning uses Blockchain in self-managing internet-of-things networks.