A Classification Method of Unstructured P2P Multicast Video Streaming Based on SVM

Author

Liu, Chaobin ; Yang, Yuexiang ; Tang, Chuan

Author_Institution

Sch. of Comput. Sci., Nat. Univ. of Defense Technol., Changsha, China

Volume

1

fYear

2009

fDate

18-20 Nov. 2009

Firstpage

68

Lastpage

72

Abstract

The classification of unstructured P2P multicast video streaming is the premise for playing online linkage and real-time evidence in the process of network monitoring management. A new classification method is demonstrated, and some real-time protocol behavior features are figured in this paper, which is found out through distinguishing packet type and transmission direction. With these accessible features a multi-classification support vector machine is built to identify applications of unstructured P2P multicast video streaming. The result of experiment shows that the method has high identification accuracy and satisfying real-time characteristic.

Keywords

multicast communication; multimedia communication; peer-to-peer computing; protocols; signal classification; support vector machines; video streaming; multi-classification support vector machine; network monitoring management; packet type; protocol behavior feature; real-time evidence; transmission direction; unstructured P2P multicast video streaming; Computer security; Electronic mail; IPTV; Information security; Monitoring; Multicast protocols; Payloads; Streaming media; Support vector machine classification; Support vector machines; SVM; behavior feature; classification; unstructured P2P multicast video streaming;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia Information Networking and Security, 2009. MINES '09. International Conference on

Conference_Location

Hubei

Print_ISBN

978-0-7695-3843-3

Electronic_ISBN

978-1-4244-5068-8

Type

conf

DOI

10.1109/MINES.2009.28

Filename

5368988