Knowledge-driven cybersecurity intelligence: software vulnerability co-exploitation behaviour discovery
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Yin, Jiao 
ORCID: https://orcid.org/0000-0002-0269-2624, Tang, MJ, Cao, Jinli ORCID: https://orcid.org/0000-0002-0221-6361, You, Mingshan ORCID: https://orcid.org/0000-0003-0958-528X, Wang, Hua ORCID: https://orcid.org/0000-0002-8465-0996 and Alazab, Mamoun ORCID: https://orcid.org/0000-0002-1928-3704
(2022)
Knowledge-driven cybersecurity intelligence: software vulnerability co-exploitation behaviour discovery.
IEEE Transactions on Industrial Informatics.
pp. 1-9.
ISSN 1551-3203
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| Item type | Article |
| URI | https://vuir.vu.edu.au/id/eprint/44498 |
| DOI | 10.1109/TII.2022.3192027 |
| Official URL | https://ieeexplore.ieee.org/document/9832800 |
| 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 | cyber security, software vulnerability, Modality-Aware Graph Convolutional Network, MAGCN, Graph Knowledge Transfer Learning, GKTL |
| Citations in Scopus | 1 - View on Scopus |
| Download/View statistics | View download statistics for this item |
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