Network Intrusion Detection through Stacking Dilated Convolutional Autoencoders

Table 10

Evaluation results on different numbers of convolutional layers and two types of activation functions.

Number of layers	Activation function	Accuracy (%)	Run time (minutes)	Parameter setting
	Sigmoid	98.83	102.83	filter_dilation = ,
				filter_shape = ,
	ReLU	98.98	57.09	feature_maps = ,
				full_units = 640.
	Sigmoid	98.78	217.25	filter_dilation = ,
				filter_shape = ,
	ReLU	98.61	60.64	feature_maps = ,
				full_units = 960.
	Sigmoid	98.80	178.26	filter_dilation = ,
				filter_shape = ,
	ReLU	98.51	48.65	feature_maps = ,
				full_units = 690.