BLOCKCHAIN AND MACHINE LEARNING INTEGRATION FOR ENHANCING IOT CYBERSECURITY IN DISTRIBUTED IOT-DRIVEN INFORMATION TECHNOLOGY ECOSYSTEMS

The fusion between Blockchain technology and Machine Learning capabilities creates a complete system that improves distributed Internet of Things security by building a new operational model. Modern security systems fall short when applied to IoT deployments because of their size and diverse system types along with limited operational resources. The research analyzes the implementation of Blockchain and Machine Learning for building an adaptive security framework that enhances resilience in IoT systems. The proposed security framework utilizes Blockchain technology’s distributed ledger system combined with artificial intelligence algorithms to guarantee data reliability along with protected communication features and traceable audit logs. The research evaluates different approaches for integration architecture and consensus systems and suitable Machine Learning models in IoT security applications.