Real-Time Traffic Monitoring and Request Blocking Firewall for Network Security
Jinna Kruthika, Gajele Manisha, Mohammad Shinaz Bhanu, Ganjikunta Abhinaya, Kuraganti Rathnababu · 2025
The increasing complexity of Distributed Denial of Service attacks threatens network security, overwhelming resources and disrupting services. Conventional firewalls falter against these dynamic threats, requiring advanced real-time solutions. This paper presents a firewall system designed for real-time traffic inspection and request blocking to enhance network security. Combining machine learning with packet inspection and iptables-based filtering, it dynamically blocks malicious Internet Protocols. Logistic regression classifies traffic as malicious using features like packet count, with Scapy enabling sniffing. A Flask-based web interface helps administrators in monitor and manage attacks, supported by email alerts for rapid response. Experiments show it outperforms traditional firewalls against Distributed Denial of Service attacks with low false positives. Tested under heavy traffic, it proves scalable. While effective for known threats, future anomaly detection could address zero-day attacks. This scalable, automated solution bridges legacy and intelligent security frameworks, providing actionable insights.