Identi�cation of encrypted and malicious network tra�c based on one-dimensional convolutional neural network

HIGHLIGHTS

• who: Conversion et al. from the Qilu University of Technology (Shandong Academy of Sciences) have published the research work: Identiufffdcation of Encrypted and Malicious Network Traufffdc Based on One-Dimensional Convolutional Neural Network, in the Journal: (JOURNAL)
• what: According to the works published recently, the methods of identifying network traffic mostly focused on the training of machine_learning models, such as convolutional neural_networks, recurrent neural_networks, decision trees, etc. In this paper, a lightweight neural_network model is designed to identify classified network traffic data types. From Table 4, the model proposed in this paper is superior to . . .
  

   

  

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