Analysis of LSTM-RNN Based on Attack Type of KDD-99 Dataset

Method and model of machine learning have applied to many industry fields. Employing RNN to detect and recognize network events and intrusions is extensively studied. This paper divides KDD-99 dataset into 4 subsets according to data item’s ‘attack type’ field. And then, LSTM-RNN is trained and verified on each subset in order to optimize model parameters. Experiments show the strategy of training for LSTM-RNN could boost model accuracy.

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