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authorLuca Deri <lucaderi@users.noreply.github.com>2024-10-26 21:19:11 +0200
committerGitHub <noreply@github.com>2024-10-26 21:19:11 +0200
commit4481ecd4c0fd896618d3a89abcc3c0bf74f2819f (patch)
treeeb2babb65cc242874ed7469d9b76ca40d7b8762c /dga/README.md
parentf5d903caadb00b3e2f68c74cf9da7a19cf4545f7 (diff)
Added reference to the existing nDPI DGA code
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diff --git a/dga/README.md b/dga/README.md
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@@ -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
-``` \ No newline at end of file
+```