AI-Driven Blockchain Framework for Trustworthy Data Sharing in IoT Ecosystems

Abstract: The proliferation of Internet of Things (IoT) infrastructures has accelerated the generation of sensitive, high- volume data across diverse sectors, ranging from healthcare and agriculture to industrial automation and smart mobility. Despite these advancements, the heterogeneity of devices, constrained computational resources, and evolving cyber threats pose significant barriers to secure and reliable data exchange. This study introduces an AI-empowered blockchain framework designed to reinforce trust management and enable transparent communication within distributed IoT environments. The proposed architecture integrates machine learning–driven trust evaluation with a novel Proof-of-Trust (PoT) consensus protocol, ensuring that nodes with verified reliability are prioritized in block validation. By embedding adaptive intelligence into blockchain operations, the framework reduces computational overhead while preserving immutability and accountability. Furthermore, distributed computing at the edge and fog layers enhances scalability and minimizes latency, making the system viable for real-time IoT applications. Simulation outcomes reveal notable improvements, including reduced transaction delays, heightened accuracy in malicious node detection, and stable performance under dense network conditions. The synergy of artificial intelligence, blockchain, and distributed computing establishes a resilient foundation for secure IoT ecosystems, paving the way for trustworthy data sharing in next-generation smart infrastructures.

Keywords: Trust Management, Artificial Intelligence, Blockchain, Distributed Computing