Framework to Uncover Threats in Social Networks Through Network Packet Visualisation
Prashant Upadhyay, Preeti Dubey, Amit Kumar Upadhyay, Nikiema Flavio · BENTHAM SCIENCE PUBLISHERS eBooks · 2025
With the increasing volume and complexity of network traffic in social networks, extracting meaningful insights from this data has become increasingly challenging. This paper presents a lightweight approach for analysing network traffic for social networks that enables the identification of patterns and anomalies that may indicate malicious activity. The paper starts by discussing the importance of network traffic visualisation and the challenges associated with it. It then provides an overview of the key components of network traffic data and various visualisation techniques that can be used to gain insights into network behaviour. The focus is on lightweight visualisation techniques that can be used to analyse network packet data for threat detection. Time series plots, scatter plots, heatmaps, and network graphs are some of the visualisation techniques that can be used to identify patterns and anomalies in network traffic for social networks. The lightweight nature of this approach enables efficient processing and analysis of large and complex datasets. In conclusion, analysing and visualizing network packet data is a crucial technique for identifying potential security threats, and a lightweight approach can enable efficient processing and analysis of large and complex network traffic of social networks. By using the techniques and tools presented in this paper, network administrators and researchers can gain valuable insights into network behaviour and identify potential security threats.