A Study on Historical Behaviour Enabled Insider Threat Prediction
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Xiao, Fan 
ORCID: https://orcid.org/0009-0007-0517-173X, Hong, Wei ORCID: https://orcid.org/0000-0003-2833-9228, Yin, Jiao ORCID: https://orcid.org/0000-0002-0269-2624, Wang, Hua ORCID: https://orcid.org/0000-0002-8465-0996, Cao, Jinli ORCID: https://orcid.org/0000-0002-0221-6361 and Zhang, Yanchun ORCID: https://orcid.org/0000-0002-5094-5980
(2024)
A Study on Historical Behaviour Enabled Insider Threat Prediction.
In:
Web and Big Data: 7th International Joint Conference, APWeb-WAIM 2023 Wuhan, China, October 6–8, 2023, Proceedings, Part III.
Song, X, Feng, R, Chen, Y, Li, J and Min, G, eds.
Lecture Notes in Computer Science, 14333
.
Springer, pp. 464-476.
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| Item type | Book Section |
| URI | https://vu-9.eprints-hosting.org/id/eprint/48883 |
| DOI | 10.1007/978-981-97-2387-4_31 |
| Official URL | https://link.springer.com/chapter/10.1007/978-981-... |
| ISBN | 9789819723867 |
| Subjects | Current > FOR (2020) Classification > 4604 Cybersecurity and privacy Current > FOR (2020) Classification > 4611 Machine learning Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
| Download/View statistics | View download statistics for this item |
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