Development of a machine-learning intrusion detection system and testing of its performance using a generative adversarial network

HIGHLIGHTS

• who: Andrei-Grigore Mari et al. from the Communications Department, Technical University of Cluj-Napoca, Cluj-Napoca, Romania have published the Article: Development of a Machine-Learning Intrusion Detection System and Testing of Its Performance Using a Generative Adversarial Network, in the Journal: Sensors 2023, 1315 of /2023/
• what: The authors focused on one such model involving several algorithms and used the NSL-KDD dataset as a benchmark to train and evaluate its performance. The authors demonstrate a way to create adversarial instances of network traffic that can be used to evade detection by a . . .
  

   

  

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