(untitled) (Journal of Artificial Intelligence & Research, 2024)
The integration of Internet of Things (IoT) devices with blockchain technology has emerged as a promising solution to enhance the security, scalability, and transparency of IoT networks. One of the critical challenges in this integration is key management, particularly the dynamic management of cryptographic keys for secure communication between devices. Traditional static key management methods are insufficient in the dynamic and decentralized nature of IoT environments. This paper explores the design and application of artificial intelligence (AI) models for dynamic key management in blockchain-integrated IoT systems. The paper discusses the role of AI in adapting to changing network conditions, optimizing key generation and distribution processes, and ensuring the secure and efficient handling of cryptographic keys. It also addresses the challenges of scalability, real-time adaptability, and resource constraints in IoT environments. Through the implementation of machine learning and deep learning models, dynamic key management systems can better protect IoT devices against evolving security threats while maintaining the benefits of blockchain’s decentralized nature. The paper concludes by outlining future research directions, including the integration of AI with advanced cryptographic protocols and the potential for cross-layer security mechanisms.