This model is a fine-tuned version of
distilbert-base-uncased on the AIT Log Data Set V2.0 dataset
1,
https://zenodo.org/records/5789064.
It achieves the following results on the evaluation set:
This model is meant for text classification of log files for network intrusion detection. The python package that runs this model can be found here ->
https://github.com/Isaacwilliam4/INSyT.
As mentioned on their site, this model was trained on the following logs: Apache access and error logs, authentication logs, DNS logs, VPN logs, audit logs, Suricata logs, network traffic packet captures, horde logs, exim logs, syslog, and system monitoring logs.
[1]M. Landauer, F. Skopik, M. Frank, W. Hotwagner, M. Wurzenbergerand A. Rauber, “AIT Log Data Set V2.0”. Zenodo, Feb. 24, 2022. doi: 10.5281/zenodo.5789064.
