FCNN: An Efficient Intrusion Detection Method Based on Raw Network Traffic

Table 2

CNN model.

Sequence	Description
1	Convolution layer (48 units, kernel size: 3, activation function: ReLU)
2	Dropout layer (dropout rate: 0.1)
3	Convolution layer (48 units, kernel size: 3, activation function: ReLU)
4	Pooled layer (size: 2)
5	Convolution layer (128 units, kernel size: 3, activation function: ReLU)
6	Dropout layer (dropout rate: 0.1)
7	Convolution layer (128 units, kernel size: 3, activation function: ReLU)
8	Pooled layer (size: 2)
9	Flatten layer
10	Dense layer (128 units, kernel size: 3, activation function: ReLU)
11	Dropout layer (dropout rate: 0.1)
12	Dense layer (1 unit, activation function: sigmoid)