| Title | An Improved Data Provenance Framework Integrating Blockchain and PROV Model |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Song, ZHANG, Yang, Li, Gaoyang, LI, Han, YU, Baozhong, HAO, Jinwei, SONG, Jingang, FAN |
| Conference Name | 2020 International Conference on Computer Science and Management Technology (ICCSMT) |
| Keywords | blockchain, Computational modeling, Computer science, Data models, data provenance, Economics, Encryption, Human Behavior, human factors, Metrics, PROV model, pubcrawl, Resistance, Scalability, Tamper resistance |
| Abstract | Data tracing is an important topic in the era of digital economy when data are considered as one of the core factors in economic activities. However, the current data traceability systems often fail to obtain public trust due to their centralization and opaqueness. Blockchain possesses natural technical features such as data tampering resistance, anonymity, encryption security, etc., and shows great potential of improving the data tracing credibility. In this paper, we propose a blockchain-PROV-based multi-center data provenance solution in where the PROV model standardizes the data record storage and provenance on the blockchain automatically and intelligently. The solution improves the transparency and credibility of the provenance data, such as to help the efficient control and open sharing of data assets. |
| DOI | 10.1109/ICCSMT51754.2020.00073 |
| Citation Key | song_improved_2020 |
An Improved Data Provenance Framework Integrating Blockchain and PROV Model