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bianyuanop/SimCLR-on-CICIDS2017

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This is a project that

  • replicates an exisiting method that utilize SimCLR on intrusion detection
  • replace the backbone network of the extractor to MLP

In the files of experiment-<model-name>.ipynb, we hyperparameter searched the best params to be evaluate the performance

In the files of train-<model-name>.ipynb, we trained the models with best params and saved the preprocessor and the models along with 5-step-wise checkpoints.

In the files of eval.ipynb, we evaluate the resnet based extractor(original) and the MLP based extractor(ours) on a set of classic ML classifiers.

All the other files are clearly named the intent so no more introduction to those files.

Conclusion

We found

  • It’s possible to use an extractor with a simpler backbone network to substitute.
  • The extractor with a simpler backbone network perform similar when on non-linear learning methods and not- learning-based methods while perform worse on linear learning methods.
  • It significantly(^10) reduces the computation resources needed by a feature extractor.

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