Integration of Blockchain and Machine Learning Techniques to Enhance IoT Security

Abstract

The rapid evolution of the Internet of Things (IoT) has revolutionized various industries, enhancing connectivity and automation. However, security concerns remain a significant challenge due to the massive data exchanges and the increasing sophistication of cyber threats. This paper explores the integration of blockchain and machine learning techniques to enhance IoT security.  Blockchain provides a decentralized and tamper-proof ledger, ensuring data integrity and security, while machine learning enables proactive threat detection and anomaly identification. By leveraging these technologies, the study proposes a robust security framework that can effectively mitigate IoT vulnerabilities. The research highlights key challenges, potential solutions, and the effectiveness of combining blockchain with machine learning in securing IoT ecosystems.