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author | Luca Deri <lucaderi@users.noreply.github.com> | 2024-10-26 21:19:11 +0200 |
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committer | GitHub <noreply@github.com> | 2024-10-26 21:19:11 +0200 |
commit | 4481ecd4c0fd896618d3a89abcc3c0bf74f2819f (patch) | |
tree | eb2babb65cc242874ed7469d9b76ca40d7b8762c /dga/README.md | |
parent | f5d903caadb00b3e2f68c74cf9da7a19cf4545f7 (diff) |
Added reference to the existing nDPI DGA code
Diffstat (limited to 'dga/README.md')
-rw-r--r-- | dga/README.md | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/dga/README.md b/dga/README.md index a999a067e..1ea4323f9 100644 --- a/dga/README.md +++ b/dga/README.md @@ -1,8 +1,8 @@ # Overview -This folder contains training and inference scripts for two models based on different technologies: MLP (multi-layer perceptron) using scikit-learn and an LSTM-based neural network using TensorFlow. Each model has its own folder with its own training and testing scripts. +This folder contains training and inference scripts for two models based on different technologies: MLP (multi-layer perceptron) using scikit-learn and an LSTM-based neural network using TensorFlow. Each model has its own folder with training and testing scripts. Developers interested in DGA detection in nDPI should also visit [this folder](../tests/dga) containing the original ML implementation. -The test scripts are only intended to show how to use an already trained model. +The test scripts only show how to use an already-trained model. ## Requirements @@ -52,4 +52,4 @@ Once training is complete, you can run inference on the test set with ```bash python tensorflow_tests/test_script.py -```
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