Paper Info
Title
Multi-Level P2p Traffic Classification Using Heuristic And Statistical-Based Techniques: A Hybrid Approach
Abstract
Peer-to-peer (P2P) applications have been popular among users for more than a decade. They consume a lot of network bandwidth, due to the fact that network administrators face several issues such as congestion, security, managing resources, etc. Hence, its accurate classification will allow them to maintain a Quality of Service for various applications. Conventional classification techniques, i.e., port-based and payload-based techniques alone, have proved ineffective in accurately classifying P2P traffic as they possess significant limitations. As new P2P applications keep emerging and existing applications change their communication patterns, a single classification approach may not be sufficient to classify P2P traffic with high accuracy. Therefore, a multi-level P2P traffic classification technique is proposed in this paper, which utilizes the benefits of both heuristic and statistical-based techniques. By analyzing the behavior of various P2P applications, some heuristic rules have been proposed to classify P2P traffic. The traffic which remains unclassified as P2P undergoes further analysis, where statistical-features of traffic are used with the C4.5 decision tree for P2P classification. The proposed technique classifies P2P traffic with high accuracy (i.e., 98.30%), works with both TCP and UDP traffic, and is not affected even if the traffic is encrypted.
Year
DOI
Venue
2020
10.3390/sym12122117
SYMMETRY-BASEL
Keywords
DocType
Volume
heuristic-based classification, multi-level P2P traffic classification, P2P-port based classification, statistical-based classification
Journal
12
Issue
Citations 
PageRank 
12
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Max Bhatia100.34
Vikrant Sharma200.34
Parminder Singh300.34
Mehedi Masud47726.95