REAL-TIME NETWORK BEHAVIOUR INTELLIGENCE
Author
Ashaithambi M,Mukeshkumar R, Naga Arjun N, Surendiran M G, Vishnukumar S S
Abstract
Computer networks support communication between devices, applications, servers, and online services. Increasing network usage also creates a need for continuous monitoring and early identification of suspicious activities. This paper presents Real-Time Network Behaviour Intelligence, a Python-based network monitoring system that captures live packets using the Scapy library and analyzes their characteristics. The system extracts source and destination IP addresses, protocols, port numbers, packet sizes, and timestamps. It monitors traffic volume, connection frequency, and port activity to understand normal network behaviour and identify unusual patterns such as sudden traffic spikes, excessive connection attempts, and suspicious port usage. Detected abnormal behaviour can generate security alerts, while a web-based dashboard presents packet information, traffic patterns, anomalies, and alerts in an organized interface. The system combines packet capture, feature extraction, behavioural analysis, anomaly detection, and visualization to improve network visibility and support investigation of potential security issues. A detected anomaly indicates a potential risk and does not, by itself, confirm that an attack has occurred.
Keywords
Real-Time Network Monitoring, Network Behaviour Analysis, Scapy, Python, Packet Capture, Anomaly Detection, Network Security, Dashboard Visualization.
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References
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