Identifying file-sharing P2P traffic based on traffic characteristics

中国邮电高校学报(英文) ›› 2008, Vol. 15 ›› Issue (4): 112-120.doi:

Identifying file-sharing P2P traffic based on traffic characteristics

成卫青,龚俭,丁伟

College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210003, China

收稿日期:2008-04-01 修回日期:1900-01-01 出版日期:2008-12-30
通讯作者: 成卫青

Identifying file-sharing P2P traffic based on traffic characteristics

CHENG Wei-qing, GONG Jian, DING Wei

College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210003, China

Received:2008-04-01 Revised:1900-01-01 Online:2008-12-30
Contact: CHENG Wei-qing,

摘要/Abstract

摘要：

This article focuses on identifying file-sharing peer-to-peer (P2P) (such as BitTorrent (BT)) traffic at the borders of a stub network. By analyzing protocols and traffic of applications, it is found that file-sharing P2P traffic of a single user differs greatly from traditional and other P2P (such as QQ) applications’ traffic in the distribution of involved remote hosts and remote ports. Therefore, a method based on discreteness of remote hosts (RHD) and discreteness of remote ports (RPD) is proposed to identify BT-like traffic. This method only relies on flow information of each user host in a stub network, and no packet payload needs to be monitored. At intervals, instant RHD for concurrent transmission control protocol and user datagram protocol flows for each host are calculated respectively through grouping flows by the stub network that the remote host of each flow belongs to. On given conditions, instant RPD are calculated through grouping flows by the remote port to amend instant RHD. Whether a host has been using a BT-like application or not can be deduced from instant RHD or average RHD for a period of time. The proposed method based on traffic characteristics is more suitable for identifying protean file-sharing P2P traffic than content-based methods. Experimental results show that this method is effective with high accuracy.

关键词:

traffic;identification,;concurrent;flows,;P2P,;discreteness;of;remote;hosts,;discreteness;of;remote;ports

Abstract:

Key words:

traffic identification;concurrent flows;P2P;discreteness of remote hosts;discreteness of remote ports

CHENG Wei-qing, GONG Jian, DING Wei. Identifying file-sharing P2P traffic based on traffic characteristics[J]. Acta Metallurgica Sinica(English letters), 2008, 15(4): 112-120.

参考文献

1. BitTorrent. 2005, http://wiki.bitcomet.com/help-zh/ tracker (in Chinese)

2. Sung L, Li H. Neighbor selection strategies for P2P systems using tit-for-tat exchange algorithm. 2005, http://www. cs.uwa terloo.ca/~lgasung/

3. PPLive. 2006, http://www.pplive.com/zh-cn/index.html (in Chinese)

4. Network-based application recognition and distributed network-based application recognition. 2005, http://www.cisco.com/en/US/products/ ps6616/ productsios_protocol_grou p_home.html

5. BitTorrent will not be blocked and telecom providers are planning to charge by traffic. 2005, http://tele com.chinabyte.com/191/2129691.shtml (in Chinese)

6. Spognardi A, Lucarelli A, DiPietro R. A methodology for P2P file-sharing traffic detection. Proceedings of Second International Workshop on Hot Topics in Peer-to-Peer Systems (HOT-P2P 2005), Jul 21, 2005, San Diego, CA, USA. 2005: 52-61

7. Milojicic D, Kalogeraki V, Lukose R, et al. Peer-to-peer computing. 2003, http://www.hpl.hp.com/techreports/ 2002/HPL-2002-57R1.pdf

8. Choi T, Kim C, Yoon S, et al. Content-aware Internet application traffic measurement and analysis. Proceedings of IEEE/IFIP Network Operations and Management Symposium (NOMS 2004), Apr 19-23, 2004, Seoul, Korea. 2004: 511-524

9. Moore A, Papagiannaki K. Toward the accurate identification of network applications. Proceedings of Passive and Active Measurement Workshop 2005 (PAM2005), Mar 31-Apr 1, 2005, Boston, MA, USA. 2005: 41-54

10. Sen S, Spatscheck O, Wang D. Accurate, scalable in-network identification of P2P traffic using application signatures. Proceedings of the 13th international conference on World Wide Web (WWW 2004), May 17-22, 2004, New York, NY, USA. 2004: 512-521

11. Haffner P, Sen S, Spatscheck O, et al. ACAS: automated construction of application signatures. Proceedings of ACM SIGCOMM workshop on Mining network data. Aug 22-26, 2005, Philadelphia, PA, USA. New York, NY, USA: ACM, 2005: 197-202

12. Chou S C. Network behavior analysis and performance evaluation of peer-to-peer application. Taipei, China: National Taiwan University, 2004 (in Chinese)

13. Karagiannis T, Broido A, Faloutsos M, et al. Transport layer identification of P2P traffic. 2004 ACM SIGCOMM Internet Measurement Conference (IMC 2004), Oct 25-27, 2004, Taormina, Sicily, Italy. 2004: 121-134

14. Karagiannis T, Papagiannaki K, Faloutsos M. BLINC: Multilevel traffic classification in the dark. Proceedings of ACM SIGCOMM. Aug 22-26, 2005, Philadelphia, PA, USA. 2005: 229-240

15. Bernaille L, Teixeira R, Akodkenou I, et al. Traffic classification on the fly. Computer Communication Review, 2006, 36(2): 23-26

16. Sadasivan G, Brownlee N, Claise B, et al. Architecture for IP flow information export. 2006, http://www.ietf.org/ internet-drafts/draft-ietf- ipfix-architecture-12.txt

17. Egevang K, Francis P. The IP Network Address Translator (NAT). RFC1631. 1994

18. Senie D. Network Address Translator (NAT)-friendly application design guidelines. RFC3235. 2002

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Identifying file-sharing P2P traffic based on traffic characteristics

Identifying file-sharing P2P traffic based on traffic characteristics

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