Identifying P2P traffic: A survey

Abstract

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.

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

“…Accordingly, the flow-details are added in the P2P flow table and the destination-IP-table is updated. Although it is known that the port-based technique is inefficient in traffic classification, it has been used here for the purpose of performing an early classification of the P2P traffic, which may not be masquerading and still using well-known P2P port numbers [6,7] for communication.…”

“…goto step 17 (6) else if (flw.fh == true) (7) write: flw → P2P (8) else ( 9) { ( 10) fset = flw.ff (11) rst = flw.MLA (fset) (12) if (rst == "P2P") (13) write: flw → P2P ( 14) else (15) write: flw → non-P2P ( 16) } ( 17) flw = fetch_flow() ( 18) }while (flw ! = NULL) End…”

“…Conventional network devices cannot handle the traffic of P2P applications, due to the fact that network administrators and ISPs face various challenges such as providing excellent broadband experience to customers, purchasing of backbone links, and upstreaming bandwidth, which are costly. Nowadays, classifying P2P traffic accurately is a difficult task as various P2P applications, either masquerade or encrypt their traffic to avoid detection [6,7]. There are some techniques for classifying the network traffic, such as port-based, payload-based, and Classification in the Dark (which includes statistical-based, pattern, or heuristic-based techniques) [7][8][9].…”

“…The main aim of this paper is to propose a hybrid technique for P2P traffic classification, which accomplishes the following tasks: Nowadays, classifying P2P traffic accurately is a difficult task as various P2P applications, either masquerade or encrypt their traffic to avoid detection [6,7]. There are some techniques for classifying the network traffic, such as port-based, payload-based, and Classification in the Dark (which includes statistical-based, pattern, or heuristic-based techniques) [7][8][9].…”

“…The main aim of this paper is to propose a hybrid technique for P2P traffic classification, which accomplishes the following tasks: Nowadays, classifying P2P traffic accurately is a difficult task as various P2P applications, either masquerade or encrypt their traffic to avoid detection [6,7]. There are some techniques for classifying the network traffic, such as port-based, payload-based, and Classification in the Dark (which includes statistical-based, pattern, or heuristic-based techniques) [7][8][9]. Since many P2P applications are masquerading their traffic either by disguising port numbers or encrypting payloads, port-based and payload-based techniques are inefficient in accurately classifying P2P traffic.…”