Block-chain and Artificial Intelligence Integration in IoT Security Framework Design

Abstract

The exponential growth of Internet of Things (IoT) devices has introduced significant security challenges, necessitating robust frameworks to protect these interconnected systems. This research presents a novel security framework that integrates block-chain technology and artificial intelligence (AI) to enhance IoT security. The framework leverages block-chain's immutability and distributed consensus mechanisms alongside AI's predictive capabilities to create a multi-layered security approach. Through experimental validation on a simulated smart home environment with 500 IoT devices, the framework demonstrated a 94.7% detection rate for security threats while reducing false positives by 78% compared to traditional security systems. Performance analysis showed that the proposed framework maintained network latency below 150ms even under high-traffic conditions, with computational overhead increases of only 12% compared to conventional security implementations. This research establishes the viability of combining block-chain and AI for real-time threat detection, secure data transmission, and autonomous decision-making in IoT environments, setting the foundation for more resilient IoT security architectures..