Anomaly-Detection
CICIDS2017 dataset
Pytorch platform
Model 1：KNN
"MergeFiles.py" implements the merging of multiple csv files.
"HoldOut.py" realizes the division of training set and test set by hold out method.
"KNNClassifier.py" establishes K-Nearest Neighbor(KNN) model to achieve anomaly detection.
Model 2：RNN
"MergeFiles.py" implements the merging of multiple csv files.
"Dataset_to_Dataloader.py"turns a csv file into a Pytorch dataloader used for network training and testing.
"LSTM.py"establishes Long Short-Term Memory(LSTM) model to achieve anomaly detection.
"Multiple_LSTM.py"establishes Long Short-Term Memory(LSTM) model to achieve multi-class classification.