--- layout: default --- # Phishing Detection Model Performance ## Overview This project develops a machine learning model for detecting phishing URLs using URLScan.io API data. ## Model Performance Over Time ### Performance Metrics Track how the model's performance evolves over time to identify improvements or degradation. ![Performance Over Time](images/performance_over_time.png) ### Confusion Matrix Latest model confusion matrix showing prediction accuracy across classes. ![Confusion Matrix](images/confusion_matrix.png) ### Feature Drift Detection Monitor feature drift to detect changes in data distribution that may affect model performance. ![Feature Drift](images/feature_drift.png) ## Dataset Information - **Source**: URLScan.io API + Phishing URL datasets - **Training samples**: TBD - **Test samples**: TBD - **Features**: TBD ## Model Architecture Details about the model architecture, feature engineering, and training process will be documented here. ## Latest Updates Check back for updates on model performance and improvements. --- _Last updated: {{ site.time | date: "%Y-%m-%d" }}_