Name
Abstract | ||
|---|---|---|
Role mining has been extensively used to automatically generate roles for role-based access control. Nevertheless, the two core problems in role mining, role minimization and edge concentration, are both NP-hard. While many approximate algorithms have been developed to solve the problems, experimental tests disclose that no algorithm clearly outperforms the others in both role minimization and edg... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TIFS.2016.2594137 | IEEE Transactions on Information Forensics and Security |
Keywords | Field | DocType |
Minimization,Access control,Bipartite graph,Business,Computer science,Upper bound | Overhead (computing),Database-centric architecture,Data mining,Upper and lower bounds,Computer science,Bipartite graph,Minification,Access control,Artificial intelligence,Data mining algorithm,Machine learning | Journal |
Volume | Issue | ISSN |
11 | 12 | 1556-6013 |
Citations | PageRank | References |
1 | 0.36 | 25 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| L Dong | 1 | 210 | 30.65 |
| Kui Wu | 2 | 32 | 6.79 |
| Guoming Tang | 3 | 67 | 17.62 |