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.