Interactive Web-Based Visual Analysis on Network Traffic Data

• Published in: Information (Basel) Vol. 14; no. 1; p. 16
• Main Authors: Jeong, Dong Hyun, Cho, Jin-Hee, Chen, Feng, Kaplan, Lance, Jøsang, Audun, Ji, Soo-Yeon
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-01-2023
• Subjects: Case studies; Communications traffic; Data analysis; discrete wavelet transformation; Feature extraction; Graph representations; Interactive systems; Network analysis; Network security; Principal components analysis; Time series; uncertainty; Visualization; Wavelet transforms; web-based visual analysis
• ISSN: 2078-2489; 2078-2489
• DOI: 10.3390/info14010016

Network traffic data analysis is important for securing our computing environment and data. However, analyzing network traffic data requires tremendous effort because of the complexity of continuously changing network traffic patterns. To assist the user in better understanding and analyzing the network traffic data, an interactive web-based visualization system is designed using multiple coordinated views, supporting a rich set of user interactions. For advancing the capability of analyzing network traffic data, feature extraction is considered along with uncertainty quantification to help the user make precise analyses. The system allows the user to perform a continuous visual analysis by requesting incrementally new subsets of data with updated visual representation. Case studies have been performed to determine the effectiveness of the system. The results from the case studies support that the system is well designed to understand network traffic data by identifying abnormal network traffic patterns.