Vulnerability exploitation time prediction: an integrated framework for dynamic imbalanced learning
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Yin, Jiao 
ORCID: 0000-0002-0269-2624, Tang, MJ, Cao, Jinli ORCID: 0000-0002-0221-6361, Wang, Hua ORCID: 0000-0002-8465-0996, You, Mingshan ORCID: 0000-0003-0958-528X and Lin, Yongzheng
(2021)
Vulnerability exploitation time prediction: an integrated framework for dynamic imbalanced learning.
Special Issue on Web Information Systems Engineering 2020, 25.
pp. 401-423.
ISSN 1386-145X
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| Additional Information | This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s11280-021-00909-z |
| Item type | Article |
| URI | https://vuir.vu.edu.au/id/eprint/44497 |
| DOI | 10.1007/s11280-021-00909-z |
| Official URL | https://link.springer.com/article/10.1007/s11280-0... |
| Subjects | Current > FOR (2020) Classification > 4602 Artificial intelligence Current > FOR (2020) Classification > 4604 Cybersecurity and privacy Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
| Keywords | exploitation, cyber security, integrated batch learning framework |
| Citations in Scopus | 19 - View on Scopus |
| Download/View statistics | View download statistics for this item |
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