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Article type: Research Article
Authors: Sangeetha, R.a | Kuriakose, Bessy M.b | Naveen, V. Edwardc | Jenefa, A.a; * | Lincy, A.d
Affiliations: [a] Department of Computer Science and Engineering, Karunya Institute of Technology and Sciences, India | [b] Department of Computer Science and Engineering, Malla Reddy Engineering College for Women, India | [c] Department of Computer Science and Engineering, Sri Shakthi Institute of Engineering and Tech, India | [d] Department of Computer Science and Engineering, National Engineering College, India
Correspondence: [*] Corresponding author. A. Jenefa, Department of Computer Science and Engineering, Karunya Institute of Technology and Sciences, India. E-mail: [email protected].
Abstract: Classifying VoIP (Voice over Internet Protocol) traffic is vital for optimizing network performance and Quality of Service (QoS). This study introduces the Multivariate Statistical-Based Classification (MVSC) system, designed to classify network traffic with high accuracy and efficiency. As traditional methods struggle in the diverse and complex landscape of today’s network traffic, which includes voice, video, gaming, and data, the MVSC algorithm rises to the challenge. It employs Statistical Dissemination and leverages various statistical features such as Packet Size, Inter-Arrival Statistics, Packet and Data rates, Flow Length, and Five-tuple information to create nuanced profiles of network traffic packets. These packets are then grouped into distinct clusters based on their statistical attributes through Application Flow Cluster Grouping. A unique aspect of the MVSC system is its approach to representing each application flow as points in a two-dimensional space, where distances to predefined application profiles are calculated. The nearest profile then determines the type of VoIP traffic. Experimental results using university traffic data (KU-IDS) underscore the system’s high accuracy, consistently around 98-99%. These findings affirm the system’s suitability for real-time deployment. In summary, the MVSC system offers a robust and efficient solution for VoIP traffic classification, significantly boosting network performance and QoS, and proving to be an invaluable asset in contemporary network management.
Keywords: Statistical dissemination, artificial intelligence, clustering algorithms, semi-supervised models, statistical analysis, VoIP traffic
DOI: 10.3233/JIFS-231113
Journal: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 4, pp. 9209-9223, 2024
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