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Deep Learning Models for IDS with the NSL-KDD dataset

This work is inspired to the paper "Intrusion Detection System for NSL-KDD Dataset Using Convolutional Neural Networks", DING Yalei and ZHAI Yuqingof, of 2018 2nd International Conference on Computer Science and Artificial Intelligence, which deals with the reproduction of deep learning models on the NSL-KDD dataset. The task is a classification of network attacks, based on network traffic informations.

Project Repository

  • Data - Folder containing the training and test dataset files
  • img - Folder containing the plots and the schemas images of the work
  • Best_NN - Folder with the callback file of the best NN model weigths
  • Best_CNN - Folder with the callback file of the best CNN model weights
  • NSL-KDD.ipynb - Jupyter notebook of the work
  • Documentation.pdf

References

DING, Yalei; ZHAI, Yuqing. Intrusion detection system for NSL-KDD dataset using convolutional neural networks. In: Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence. 2018. p. 81-85.

FU, Yanfang, et al. A Deep Learning Model for Network Intrusion Detection with Imbalanced Data. Electronics, 2022, 11.6: 898.

NSL-KDD dataset from the Canadian Institute for Cybersecurity https://www.unb.ca/cic/datasets/nsl.html