Vulnerability exploitation time prediction: an integrated framework for dynamic imbalanced learning

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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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 https://doi.org/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 11 - View on Scopus
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