Real-Time Network Traffic Anomaly Detection System

Design a sophisticated network traffic analysis platform using JavaScript that performs real-time anomaly detection and threat identification. Implement advanced statistical and machine learning algorithms for detecting unusual network patterns, including entropy-based analysis, clustering-based outlier detection, and time-series forecasting. Create a comprehensive visualization system that shows network topology, traffic flows, and potential security risks. Include adaptive learning capabilities that improve detection accuracy over time.