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bpf-ml's Introduction

Bringing Machine Learning to the OS Kernel

This is a Hackathon 2020 project that explores (and confirms) the possibility of evaluating machine learning models inside the Linux kernel. In this hack, we use PyTorch to train a binary classifier to distinguish between malicious and benign IP traffic and translate this model into eBPF-based XDP packet filter.

To reproduce the results:

  1. Collect some positive and negative data samples in PCAP format (e.g., using tcpdump). This repo has some sample packets in data/ directory.
  2. Train your classifier (run model/model.py script).
  3. Copy the quantized weights of your model into array w and bias b in xdp/xdp.c. (Yeah, we should've generated a source file instead)..
  4. Compile your C code and install the eBPF module by running xdp/compile_attach.sh script.
  5. To uninstall the packet filter, run xdp/remove.sh.

Please note that this project is merely a proof-of-concept hack and is not supported by the developers. Feel free to fork and move it forward, and we'll send you our kudos and PRs!

bpf-ml's People

Contributors

motus avatar maharishib avatar robin-liao avatar

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