ML BASED SYSTEM FOR NETWORK THREAT DETECTION AND RESPONSE

SOAR" system (Security Orchestration, Automation, and Response). This system seamlessly integrates a rule-based component with a Random Forest model for robust DDoS attack detection using flow-based data. The project involved collecting data through the port mirroring technique in routers, creating comprehensive flow-based data entries. Through meticulous optimization of model hyperparameters, we successfully deployed this system to detect and respond to real attacks. Additionally, I developed a web admin dashboard and a Flutter admin app to facilitate the manipulation and monitoring of the entire network, ensuring a user-friendly experience for efficient management.