This model is a train-from-scratch version of
bert-base-uncased on a mixed-source PCAP dataset.
It achieves the following results on the evaluation set:
Pretrained model with
bert-base-uncased (110M parameters) as the base architecture.
This model is mainly used to get embeddings for PCAP IPv4 header data, which can be further used for ML-based tasks e.g., classification, clustering, etc.
The usage is almost the same as regular BERT models, except that the input data is PCAP traces.
TBD.
TBD.
