Data Collection: The system collects network traffic data Monitors incoming and outgoing connections Logs system events and user activities

Analysis Pipeline: Network traffic is analyzed in real-time by the NetworkTrafficAnalyzer The ThreatAnalyzer processes this data using AI models Anomalies are detected using the Isolation Forest algorithm Deep learning models identify potential threats

Visualization Dashboard: Real-time metrics display: Active threats counter Detected anomalies Overall traffic health score Number of active connections

Interactive time-series graph showing: Threat trends over time Anomaly patterns Traffic patterns

Alert System: High-priority threats trigger immediate alerts Anomalies are logged and displayed Traffic patterns are monitored continuously