DS2PM: A Data-Sharing Privacy Protection Model Based on Blockchain and Federated Learning

With the development of big data and blockchain, an increasing number of scholars have begun to study blockchain for data sharing. By studying data sharing models that are based on blockchain, we find that almost all of them have the following problems: 1) it is difficult to protect the privacy and integrity of users' data, along with users' data ownership; 2) the storage burden of blockchain is heavy, and blockchain lacks a mechanism for dealing with data with diverse types and inconsistent formats; and 3) the consensus mechanism has low fairness or low efficiency. Therefore, we propose a data-sharing privacy protection model (DS2PM) that is based on blockchain and a federated learning mechanism for solving these problems. The safety analysis and experimental results show that the DS2PM outperforms the previously established schemes.