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Adversarial-ML-for-IDS

Summary

  • Extensive analysis and understanding of the New Gas Pipeline Dataset
  • Attacking rule based models using explainable AI techniques
  • ZOO based coordinated descent algorithm for handling binary and continuous features (+ one hot encoder + constraints + attack property preservation)
  • Analyse defense mechanisms (Model based and data based)

Files and Dir

  • data: Contains the raw dataset and the processed data used for training the deep learning models
  • src: Contains the source code for pre-processing the data and performing exploratory data analysis
  • results: Contains the results of the hyper parameter search and model comparison
  • ICS_IDS: Performs various adversarial attacks (Iterative FGSM and ZOO) and also evalutes the effectiveness of different defense strategies.

For more information about the project: final_report

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An elaborate study to determine the effects of Adversarial ML in ML/DL based Intrusion Detection Systems used in Power Plants.

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