Efficient Data Asset Right Provenance for Data Asset Trading Based on Blockchain

As a new production factor, data has become an essential asset of enterprises, and the demand for data asset trading has grown rapidly. However, existing data asset trading lacks effective and efficient provenance of data asset right changes. To this end, firstly, a provenance-oriented data asset right model DARM is designed to achieve both forward recording and reverse provenance of changes to data asset right. Secondly, through the derivation tree based on prefix tree structure and its mapping table, a blockchain-based efficient provenance method Prov-DARM for data asset right change is proposed, which can realize fast on-chain provenance of data asset right change information and form provenance tree. Finally, a key right change process is constructed on-chain that is mapped one-to-one with the entire off-chain trading process. Through the “off-chain + on-chain” hybrid storage method, the tamper-proof and provenance of data asset right change information is guaranteed, and at the same time, it reduces the pressure of storage and computation of blockchain. Experimental results show that Prov-DARM has lower query latency and higher throughput in data asset right change provenance, especially in constructing a provenance tree.