Name
Abstract | ||
|---|---|---|
The traditional data publishing methods will remove the sensitive attributes and generate the abundant records to achieve the goal of privacy protection. In the big data environment, the requirement of utilizing data (e.g., data mining) become more and more various, which is beyond the scope of the traditional method. This paper provides a cryptographic data publishing system that preserves the data integrity (i.e., the original data structure is preserved) and achieves anonymity without deletion of any attribute or utilization of redundancy. The security analysis shows that our system is secure under our proposed security model. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.jcss.2016.12.004 | Journal of Computer and System Sciences |
Keywords | Field | DocType |
Data publishing,Data privacy,Big data,Format-preserving encryption | Data structure,Data security,Computer science,Cryptography,Data integrity,Data publishing,Information privacy,Big data,Database,Computer security model | Journal |
Volume | ISSN | Citations |
89 | 0022-0000 | 5 |
PageRank | References | Authors |
0.45 | 25 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tong Li | 1 | 185 | 11.93 |
| Zheli Liu | 2 | 356 | 28.79 |
| Jin Li | 3 | 4886 | 213.21 |
| Chunfu Jia | 4 | 602 | 45.16 |
| Kuan-ching Li | 5 | 933 | 122.44 |