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Network intrusion detection with Machine Learning (Deep Learning) experiment

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net_intrusion_detection

Net intrusion detection experiment for Final Project of DeepLearning class at Inha University.

Contributions

  1. Correct Evaluation Metric
  2. Adressing data imblance
  3. Benchmark results for different ML models
  4. Running code for training/evaluating

Accompanying slides

https://docs.google.com/presentation/d/1Rjj1vF0hv8vSJWeDxk23nE4A4w3fv8tBdvsyIBpWTdU/edit?usp=sharing

5-Fold CV Results

Classifier 5-Fold Balanced Accuracy
Random Forest 84.41
Content Linear Softmax 80.99
Neural Network with 3 dense layer 84.87
Neural Network with 5 dense layer 85.57
1D-CNN with 2conv 1fc layer 87.11

Softmax

Please run the Softmax.ipynb

NN

Please run the NN.ipynb There are two NN architectures:

  1. 'nn3' - 3 layers
  2. 'nn5' - 5 layers

1D-CNN

Please run the CNN.ipynb There are two 1D-CNN architectures:

  1. 'cnn2' - 2 conv layers
  2. 'cnn5' - 5 conv layers

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Network intrusion detection with Machine Learning (Deep Learning) experiment

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  • Jupyter Notebook 92.9%
  • Python 7.1%