An improved X-means and isolation forest based methodology for network traffic anomaly detection.
Anomaly detection in network traffic is becoming a challenging task due to the complexity of large-scale networks and the proliferation of various social network applications. In the actual industrial environment, only recently obtained unlabelled data can be used as the training set. The accuracy o...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2022-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0263423 |