EBDTS: An Efficient BCoT-Based Data Trading System Using PUF for Authentication

The volume of the data generated by the Internet of Things (IoT) is expanding rapidly, primarily driven by the personal devices. However, with the severely limited memory resources and difficult security authentication processes, large amounts of the data must be abandoned. Blockchain of Things (BCoT) provides a scalable solution to these challenges by integrating blockchain and the IoT. In this paper, we propose an efficient BCoT-based data trading system using physical unclonable functions (PUFs) for authentication. PUFs are utilized for iterative keys and pseudo-identity generation to ensure the privacy and security of the IoT devices. To protect the copyright of the sellers' data, the system sets up a data arbitration center to address the issues related to the unauthorized resale of the datasets. In addition, a fuzzy comprehensive evaluation model is proposed to regulate the behavior of the data traders. Our security analysis demonstrates that the proposed system is not only secure under the ROR model but also resistant to the internal attacks. The experimental results show the reliability and the effectiveness of the proposed system.