A Novel Intelligent-Based Intrusion Detection System Approach Using Deep Multilayer Classification

Algorithm 1

Deep multilayer classification.

	Inputs: X - input dataset,
	Subsampling size
	Output: Reconstruction loss for anomaly test data
	Step 1: Initialize data = { };
	Step 2:# Initializing a MinMax Scaler
	scaler = MinMaxScaler()
	Step 3:# Instantiating the Autoencoder
	model = Autoencoder()
	# creating an early_stopping
	early_stopping = EarlyStopping(monitor = 'val_loss',
	patience = 2,
	mode = 'min')
	# Compiling the model
	model.compile(optimizer = 'Adam',
	loss = 'mae')
	Step 4: # mlp = Sequential() # initializing model
	# input layer and first layer with 50 neurons
	mlp.add(Dense(units = 50, input_dim = X_train.shape [1], activation = 'relu'))
	# output layer with softmax activation
	mlp.add(Dense(units = 5,activation = 'softmax'))