Research Article
A Novel Way to Generate Adversarial Network Traffic Samples against Network Traffic Classification
Table 6
Network structure and parameters of Vgg-16 CNN.
| | Name | Parameters |
| | Input layer | | | Convolution layer | Convolution core | | | Output | | | Batch normalization layer | Output | | | Convolution layer | Convolution core | | | Output | | | Batch normalization layer | Output | | | Max pooling layer | Sampling window | | | Output | | | Convolution layer | Convolution core | | | Output | | | Batch normalization layer | Output | | | Convolution layer | Convolution core | | | Output | | | Batch normalization layer | Output | | | Max pooling layer | Sampling window | | | Output | | | Convolution layer | Convolution core | | | Output | | | Batch normalization layer | Output | | | Flatten layer | Output | | | Full connection layer dense 1 | Output | | | Full connection layer dense 2 | Output | |
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