TY - GEN
T1 - Identification and analysis of Skype peer-to-peer traffic
AU - Zhang, Dongyan
AU - Zheng, Chao
AU - Zhang, Hongli
AU - Yu, Hongliang
PY - 2010
Y1 - 2010
N2 - More and more applications are adopting peer-to-peer (P2P) technology. Skype is a P2P based, popular VoIP software. The software works almost seamlessly across Network Address Translations (NATs) and firewalls and has better voice quality than most IM applications. The communication protocol and source code of Skype are undisclosed. It uses high strength encryption and random port number selection, which render the traditional flow identification solutions invalid. In this paper, we first obtain the Skype clients and super nodes by analyzing the process of login and calling in different network environments. Then we propose a method to identify Skype traffic based on Skype nodes and flow features. Our proposed method makes the previously hard-to-detect Skype traffic, especially voice service traffic, much easier to identify. We design an identification system utilizing the proposed method and implement the system in a LAN network. We also successfully identified Skype traffic in one of the largest Internet Providers over a period of 93 hours, during which over 30TB data were transmitted. Through experiments, we show that our proposed approach and implementations can indeed identify Skype traffic with higher accuracy and effectiveness.
AB - More and more applications are adopting peer-to-peer (P2P) technology. Skype is a P2P based, popular VoIP software. The software works almost seamlessly across Network Address Translations (NATs) and firewalls and has better voice quality than most IM applications. The communication protocol and source code of Skype are undisclosed. It uses high strength encryption and random port number selection, which render the traditional flow identification solutions invalid. In this paper, we first obtain the Skype clients and super nodes by analyzing the process of login and calling in different network environments. Then we propose a method to identify Skype traffic based on Skype nodes and flow features. Our proposed method makes the previously hard-to-detect Skype traffic, especially voice service traffic, much easier to identify. We design an identification system utilizing the proposed method and implement the system in a LAN network. We also successfully identified Skype traffic in one of the largest Internet Providers over a period of 93 hours, during which over 30TB data were transmitted. Through experiments, we show that our proposed approach and implementations can indeed identify Skype traffic with higher accuracy and effectiveness.
KW - Logging
KW - Skype
KW - Traffic identification
KW - Voice flow
UR - https://www.scopus.com/pages/publications/77954464996
U2 - 10.1109/ICIW.2010.36
DO - 10.1109/ICIW.2010.36
M3 - 会议稿件
AN - SCOPUS:77954464996
SN - 9780769540221
T3 - 5th International Conference on Internet and Web Applications and Services, ICIW 2010
SP - 200
EP - 206
BT - 5th International Conference on Internet and Web Applications and Services, ICIW 2010
T2 - 5th International Conference on Internet and Web Applications and Services, ICIW 2010
Y2 - 9 May 2010 through 15 May 2010
ER -