The Sentinel Intrusion Detection System is designed to monitor network traffic in real time, processing thousands of packets per second to detect potential threats. It uses AI-based anomaly detection algorithms to identify unusual patterns that could indicate cyber attacks. Automated alerting mechanisms reduce the need for constant manual monitoring, ensuring rapid response to incidents. The system integrates with ELK Stack for centralized logging and provides dashboards to visualize traffic anomalies. Snort is used for deep packet inspection and rule-based detection, enhancing security accuracy. Docker containers are deployed to create scalable and isolated environments. Python scripts automate log parsing, alert generation, and threat analysis workflows. The system undergoes regular penetration testing to validate its defenses. SIEM tools are integrated for incident logging, reporting, and threat management. The Sentinel system is a production-ready solution adopted by enterprise clients to strengthen network security.
Key Points:
- Real-time network monitoring and analysis.
- AI-based anomaly detection for unknown threats.
- Automated alerting system for suspicious activities.
- ELK Stack integration for logging and visualization.
- Snort integration for deep packet inspection.
- Docker deployment for scalability and isolation.
- Python automation for log parsing and alerts.
- Regular penetration testing for validation.
- SIEM integration for incident reporting.
- Enterprise-ready, production deployment.