Deep learning-based network intrusion detection systems

HIGHLIGHTS

• What: The paper discusses the strengths of these models in capturing spatial and temporal features and examines their performance on key datasets such as KDD Cup 99 and UNSW-NB15. The paper describes the research background and existing methods in the related field, followed by a detailed introduction to the architecture of the proposed hybrid model and its implementation process. The CNN-LSTM hybrid model aims to fully leverage the strengths of Convolutional Neural_Networks (CNN) in feature extraction and Long Short-Term Memory (LSTM) networks in sequence modeling. This would allow the model to automatically focus on . . .
  

   

  

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