Dynamic Threat Detection and Mitigation Using AI-Infused Firewalls
B V Abhinav, Abhirup MVNS, Adithya D. Shetty, Akash Bhat, Clara Kanmani A · 2025
This research introduces an AI-Infused Firewall that revolutionizes network security by integrating artificial intelligence to detect and mitigate evolving cyber threats. Traditional firewalls often fall short in identifying novel and sophisticated vulnerabilities. Our proposed system addresses this limitation by dynamically adapting firewall rules based on real-time network traffic analysis and employing machine learning for packet classification. Evaluated through performance metrics such as detection accuracy and response time, the system demonstrates efficient threat identification and rapid mitigation. A practical deployment scenario includes securing enterprise networks against zero-day attacks and sophisticated intrusion attempts. Through intelligent automation, the system efficiently detects potential vulnerabilities and mitigates risks by automating security responses, thereby reducing manual intervention. This approach enhances threat detection accuracy, improves overall network security posture, and demonstrates advancements in proactive threat mitigation and efficient network protection.