Dataset (CICDDDoS2019)

Data Cleaning & Preprocessing

Train-Test Split

Feature Selection

Outlier Detection & Capping

Normalization & Scaling

SMOTE Oversampling

Dimensionality Reduction (PCA, LDA, t-SNE, UMAP)

Machine Learning Models (RF, XGBoost, LightGBM, SVM etc.)

Deep Learning Models (DNN, CNN, RNN, LSTM, GRU, Transformer, CNN+LSTM)

Evaluation Metrics (Accuracy, Confusion Matrix, F1)

All Models Accuracy Ranking Comparison