An Intrusion Detection System (IDS) based on a modified version of the Self-Organizing Incremental Neural Networks, called Soft-Forgetting SOINN (SF-SOINN).

Contents:

• SOINN folder contains the SF-SOINN Python class
• nsl-kdd.ipynb is the Python notebook with the experiments on the NSL-KDD intrusion dataset
• cic-ids-2017.ipynb is the Python notebook with the experiments on the CIC-IDS-2017 intrusion dataset
• test-data folder contains a Python notebook, data_generator.ipynb, that creates the pickles of artificial 2D datasets
• artificial_tests.ipynb is a Python notebook with clustering experiments on the 2D artificial datasets

The datasets needed to run the notebooks are available at the following links:

• Canadian Institute for Cybersecurity - NSL-KDD
• Canadian Institute for Cybersecurity - CIC-IDS-2017

Implementation of the SF-SOINN network is done using igraph due to its simplicity. It is not the most performing implementation, some little improvements could make the network's operations faster, and maybe other packages like NetworkX perform better. If performances are more important than the simplicity of the code, then the network could be implemented using Tensorflow to take advantage of the processing power of GPUs.