Blockchain Integrated Intelligent Firewall System for Real Time Intrusion Detection
Rayapudi Venkata Rahul, V Sandhya, Priya Arundhati, S. Gayathri, A Yasvanth, E. Varun, Vinod L. Desai · 2025
The rapid, adaptive, and secure detection of network anomalies is critical in cybersecurity to prevent unauthorized access and malicious activities. The proposed framework integrates blockchain technology with an intrusion detection system (IDS) for real-time anomaly detection and adaptive firewall management. The primary objective is to design a system capable of monitoring network traffic, identifying threats with high sensitivity and accuracy, and ensuring tamperproof logging of security actions. Utilizing a machine learning model trained with imbalanced datasets enhanced by SMOTE, the IDS dynamically adapts detection thresholds based on traffic behavior. Blockchain integration guarantees immutable logging of anomalies and denied traffic. Scapy-based packet inspection enables feature extraction for real-time classification using a Random Forest model, while dynamic rule generation ensures responsive and secure traffic filtering. The results demonstrate the potential of this system in enhancing network security with blockchain-backed integrity, automated incident response, and adaptive threat detection capabilities. The proposed approach signifies a robust advancement in proactive cybersecurity mechanisms. for an increasingly interconnected digital world.