netFound-640M-base

Description

netFound is a network traffic foundation model that uses transformer architecture and includes a pretraining phase on unlabeled data to achieve high results.

Key features:

  • netFound takes raw PCAP data as input
  • netFound can (and need) be pretrained on the unlabeled dataset
  • netFound uses Hierarchical Transformer architecture to take into account packet burst and flow behavior
  • netFound uses burst metadata (inter arrival time, number of bytes per burst, etc)

Source code

https://github.com/SNL-UCSB/netfound

Pretraining dataset

For pretraining, we used a private real-world dataset consisting of more than 450mln network flows. The model was pretrained for approximately 1 epoch (iterated through ~480mln flows).

Checkpoint

Model: Large (16 heads, 24 hidden layers, 1024 hidden size)
Total params: 643,825,672
January 17, 2025

Paper

https://arxiv.org/abs/2310.17025

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Evaluation results