A minority class boosted framework for adaptive access control decision-making
Download
Download
Download
Full text for this resource is not available from the Research Repository.
Export
You, Mingshan 
ORCID: 0000-0003-0958-528X, Yin, Jiao ORCID: 0000-0002-0269-2624, Wang, Hua ORCID: 0000-0002-8465-0996, Cao, Jinli ORCID: 0000-0002-0221-6361 and Miao, Yuan ORCID: 0000-0002-6712-3465
(2022)
A minority class boosted framework for adaptive access control decision-making.
In: International Conference on Web Information Systems Engineering, 26 – 29 October 2021, Melbourne, Australia.
Dimensions Badge
Altmetric Badge
| Item type | Conference or Workshop Item (Paper) |
| URI | https://vuir.vu.edu.au/id/eprint/44502 |
| DOI | 10.1007/978-3-030-90888-1_12 |
| Official URL | https://link.springer.com/chapter/10.1007/978-3-03... |
| ISBN | 9783030908874 |
| Subjects | Current > FOR (2020) Classification > 4606 Distributed computing and systems software Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
| Keywords | access control, machine learning, algorithms, concept drift, problem solving |
| Citations in Scopus | 4 - View on Scopus |
| Download/View statistics | View download statistics for this item |
CORE (COnnecting REpositories)