SAEDVAE

This implementation for the paper: Learning Neural Representations for Network Anomaly Detection.

The implementation requirements: Python >= 2.7 Theano Downhill 0.3.2

We are reorganizing/cleaning the implementation. The completed code will be available soon.

NOTEBOOK: We implemented SAE on tensorflow, please see the jupyternotebook.

Name		Name	Last commit message	Last commit date
Latest commit History 50 Commits
Data		Data
Notebooks		Notebooks
Results/Exp_Hidden		Results/Exp_Hidden
__pycache__		__pycache__
BaseOneClass.py		BaseOneClass.py
BaseOneClass.pyc		BaseOneClass.pyc
Boxplot_parameter.py		Boxplot_parameter.py
Data_information.py		Data_information.py
High_dimension_visualize.py		High_dimension_visualize.py
Histogram_z.py		Histogram_z.py
Investigate_parameters.py		Investigate_parameters.py
LOF.py		LOF.py
LOF.pyc		LOF.pyc
Methods.py		Methods.py
Methods.pyc		Methods.pyc
Plot_Curves.py		Plot_Curves.py
Plot_Curves.pyc		Plot_Curves.pyc
ProcessingData.py		ProcessingData.py
ProcessingData.pyc		ProcessingData.pyc
Query_time.py		Query_time.py
README.md		README.md
S_DAE.py		S_DAE.py
S_DVAE.py		S_DVAE.py
S_ShrinkAE.py		S_ShrinkAE.py
S_VAE.py		S_VAE.py
Visualize_z.py		Visualize_z.py
compute_auc.py		compute_auc.py
dA.py		dA.py
encode_data.py		encode_data.py
hiddenLayer.py		hiddenLayer.py
hiddenLayer.pyc		hiddenLayer.pyc
logistic_sgd.py		logistic_sgd.py
loss_component.py		loss_component.py
mlp.py		mlp.py
nnet_architecture.py		nnet_architecture.py
nnet_architecture.pyc		nnet_architecture.pyc
sparsity_investigate.py		sparsity_investigate.py
stopping_para.py		stopping_para.py
stopping_para.pyc		stopping_para.pyc
utils.py		utils.py
utils.pyc		utils.pyc