/net_intrusion_detection

Network intrusion detection with Machine Learning (Deep Learning) experiment : 1d-cnn, softmax, neural networks, convolution

Primary LanguageJupyter Notebook

deep learning based network intrusion detection in PyTorch

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

dataset homepage: https://www.unb.ca/cic/datasets/ids-2017.html

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