Netflow based P2P detection in UDP traffic

Zhang, Qianli; Ma, Yunlong; Zhang, Pei; Wang, Jilong; Li, Xing

doi:10.1109/icicip.2014.7010349

Cited by 3 publications

(2 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Further the model can be employed for real-time identification of traffic. Zhang et al [67] proposed component based method to detect P2P traffic utilizing UDP for communication. In graph theory, component is defined as connected sub-graphs from a disjoint graph.…”

Section: Classification Of Traffic In the Darkmentioning

confidence: 99%

Identifying P2P traffic: A survey

Bhatia

Kumar

2016

Peer-to-Peer Netw. Appl.

View full text Add to dashboard Cite

Peer-to-Peer (P2P) traffic is widely used for the purpose of streaming media, file-sharing, instant messaging, games, software etc., which often involves copyrighted data. From the past decade, P2P traffic has been contributing to major portion of Internet traffic which is still rising and hence is consuming a lot of network traffic bandwidth. It also worsens congestion of network traffic significantly and degrades the performance of traditional client-server applications. Popularity of various P2P applications has led Internet Service Providers (ISPs) to face various challenges regarding efficiently and fairly utilizing network resources. The traditional methods of identifying P2P traffic such as port-based and payload-based are proving ineffective due to their significant limitations and can be bypassed. Hence, new approaches based on statistics or behaviour of network traffic needs to be developed and adopted in order to accurately identify existing and new P2P traffic which emerge over the time. This article presents a survey regarding various strategies involved in identifying P2P traffic. Furthermore, conceptual analysis of network traffic measurement and monitoring is also presented.

show abstract

Section: Classification Of Traffic In the Darkmentioning

confidence: 99%

Identifying P2P traffic: A survey

Bhatia

Kumar

2016

Peer-to-Peer Netw. Appl.

View full text Add to dashboard Cite

show abstract

“…The experimental results achieved precision values ranging between 90.96-93.66% and recall values ranging between 86.69-95.73% in identifying PPTV, Skype, and Thunder. Zhang et al [35] proposed the component-based technique (i.e., based on the graph theory) to analyze various P2P applications which use the UDP protocol for communication. They argue that component-level statistics can be used to detect P2P traffic reliably and accurately.…”

Section: Classification In the Darkmentioning

confidence: 99%

Multi-Level P2P Traffic Classification Using Heuristic and Statistical-Based Techniques: A Hybrid Approach

et al. 2020

View full text Add to dashboard Cite

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.

show abstract