MasterThesis

Folder Preprocessing:

• Shows the steps of how the preprocessing of the real data is done
  • the 10 downlaoded datasets of CSE-CIC-IDS2018 are loaded, then combined
  • unnecessary columns are dropped
  • preprocessing steps are carried out
    • droping nan, inf and -inf, negative values
    • changing time to UNIX format
  • aggregating and saving the classes back into different datasets
    • "BruteForce": ["FTP-BruteForce", "SSH-Bruteforce", "Brute Force -Web", "Brute Force -XSS"],
    • "DoS": ["DoS attacks-GoldenEye", "DoS attacks-Slowloris", "DoS attacks-Hulk", "DoS attacks-SlowHTTPTest", "DDoS attacks-LOIC-HTTP", "DDOS attack-HOIC", "DDOS attack-LOIC-UDP"],
    • "Infiltration": ["Infilteration"],
    • "Bot": ["Bot"],
    • "Benign": ["Benign"]

Folder Models

• contains 4 notebooks
  • SDV (GitHub repo name) notebook has CTGAN, CopulaGAN, and TVAE models more info at: https://docs.sdv.dev/sdv/single-table-data/modeling/synthesizers
  • Synthcity (GitHub repo name) notebook contains RTAVE and ADSGAN models more info at: https://github.com/vanderschaarlab/synthcity
  • TabFairGAN notebook has TabFairGAN models more info at: https://github.com/amirarsalan90/TabFairGAN
  • Combining_everthing contains the code of how synthetically generated datasets are combined into 1 dataset

Folder Classifiers

• contains the code for both Random Forest and XGBoost classifiers and the proprocessing steps

• Each cell in the notebook is explained separately.

• sdmetric (used for evaluation) can be found at: https://docs.sdv.dev/sdmetrics/

• table-evaluator (used for the evaluation) can be found at: both are found at: https://github.com/Baukebrenninkmeijer/table-evaluator