Decentralized IoT Data Trading with Subscription Model

Abstract

This paper presents a decentralized, trustless architecture for IoT data trading, leveraging a subscription-based economic model, decentralized publish/subscribe communication, and Distributed Ledger Technologies (DLTs). The system addresses scalability, integrity, confidentiality, and privacy challenges while ensuring financial incentives through end-to-end encrypted transmission and blockchain-based smart contracts. By integrating established standards and decentralized identity management, the framework secures digital rights, clarifies data ownership, and enables flexible trading mechanisms. The proposed architecture supports trustless information exchange, guarantees secrecy in IoT-based sensor data sharing, and fosters economic incentives for stakeholders. Evaluations focus on system performance, efficiency in encrypted data transmission, and trading cost optimizations. Future work includes optimizing Gas usage, enhancing broker operations, implementing a decentralized search engine for data products, and refining qualifications for data providers and brokers. This research contributes to the development of secure, scalable, and privacy-preserving IoT data trading solutions, ensuring efficient and transparent transactions.