Deep learning dga malicious domain name detection based on multi-stage feature fusion

HIGHLIGHTS

• What: The model proposed in this paper is effective for multi-class detection of DGA malicious domains. Comparative Performance of Models for Multi-Family Malicious Domain Detection Model Acc(%) Precision(%) Recall(%) F1-Score(%) LSTM[9] HDNN[16] CNN_BiLSTM[17] FEDCC[12] CT_B From Table 3, it is evident that, compared to the benchmark models, the model proposed in this paper shows the best overall performance, with both Accuracy and F1-Score exceeding 93%. This demonstrates that the model proposed in this paper, by capturing multi-level features from local to global and from surface to depth, enhances . . .
  

   

  

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