ARTIFICIAL INTELLIGENCE AND BLOCKCHAIN FOR TRUSTWORTHY INTERNET OF THINGS SECURITY: A COMPREHENSIVE FRAMEWORK

The Internet of Things (IoT) has transformed conventional computing environments by connecting physical devices, sensors, machines, and intelligent applications through communication networks. The rapid expansion of IoT has created significant opportunities in healthcare, smart cities, industrial automation, transportation, agriculture, and home automation. However, the distributed and heterogeneous nature of IoT introduces substantial security, privacy, and data-management challenges. Artificial Intelligence (AI) can provide intelligent mechanisms for detecting abnormal behavior, identifying cyber threats, and automating security decisions, while blockchain can provide decentralized trust, data integrity, and transparent transaction management. This paper investigates the integration of AI and blockchain technologies for developing trustworthy IoT security systems. A conceptual framework is proposed in which IoT devices generate data, AI models analyze device and network behavior, and blockchain provides a distributed trust layer for recording important security events and verifying data integrity. The paper examines machine learning-based anomaly detection, decentralized authentication, secure data management, privacy preservation, smart contracts, and intelligent threat response. Major challenges involving computational overhead, scalability, energy consumption, interoperability, model reliability, and blockchain storage requirements are also discussed. The study further identifies future research directions involving federated learning, edge intelligence, explainable AI, lightweight blockchain protocols, and privacy-preserving security mechanisms. The proposed integration demonstrates the potential to create more resilient and trustworthy IoT ecosystems while highlighting the need for efficient architectures suitable for resource-constrained environments.