期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

流特征的Skype流量识别 被引量：3

Skype traffic identification based on flow characteristics
在线阅读 下载PDF
导出
摘要 Skype流识别的研究大多局限于在静态载荷特征和通信机制,没有考虑网络流特征在Skype流量识别中的作用.提出了一种基于朴素贝叶斯分类的Skype流量识别模型.选择流的连接特征和实时特征作为分类特征集,根据流的连接特征组织网络流,再进一步根据流的包长度、平均发送间隔和突发带宽消耗等实时流特征识别Skype流量.在北京联通骨干网络上的实验表明该模型能有效地识别Skype流,是一种有效的Skype流识别算法. Most of the Skype traffic identification models are limited to Skype communication mechanisms and static payload characteristics. No net flow characteristics are considered in identification algorithms. To overcome this limitation, a hierarchical Skype traffic identification model based on naive Bayesian classification was developed. Flows were analyzed according to network connection modes. Results were then obtained according to real-time flow characteristics, such as packet size, average inter-packet gap and burstiness of bandwidth consumption. The validity of the algorithm was proven by testing conducted on the Beijing China Unicorn backbone network.
作者 万月亮 朱贺军 刘宏志
机构地区 北京工商大学计算机与信息工程学院 公安部第三研究所北京锐安科技有限公司
出处 《智能系统学报》 2010年第2期139-143,共5页 CAAI Transactions on Intelligent Systems
关键词 流量识别 朴素贝叶斯分类 深度包检测 实时流特征 traffic identification naive Bayesian classification deep packet inspection real-time flow characteristic
分类号 TP393.09 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献9

  • 1BASET S A,SCHULZRINNE H.An analysis of the Skype peer-to-peer internet telephony protocol[C]// IEEE Infocom'06.Barcelona,Spain,2006:1-11.
  • 2BIONDI P,DESCLAUX F.Silver needle in the Skype[C]//Black Hat Europe'06.Amsterdam,The Netherlands,2006,1:25-47.
  • 3YU Y F,LIU D D,LI J,et al.Traffic identification and overlay measurement of Skype[C]//Proc of IEEE International Conference on Computational Intelligence and Security.Guangzhou,China,2006:1043-1048.
  • 4CHEN K T,HUANG C Y,HUANG P,et al.Quantifying fying Skype user sattsfaction[C]//ACM SIGCOMM'06.Pisa,Italy,2006:399-410.
  • 5LU L,JEFFREY H,SAFAVI-NAINII R,et al.Transport layer identification of Skype traffic[C]//ICOIN 2007.Estoril,Portugal,2007:465-481.
  • 6DARIO B,MARCO M,MICHELA M.Revealing Skype traffic when randomness plays with you[C]//ACM Sigcomm'07.Kyoto,Japan,2006:37-48.
  • 7FALOUTSOS M,KARAGIANNIS C K,BROIDO A T.Transport layer identification of P2P traffic[C]// Proceedings of the 4th ACM SIGCOMM Conference on Internet Measurement.Taormina,Sicily,Italy,2004:121-134.
  • 8MOORE A,ZUEV D.Internet raffic classification using Bayesian analysis[C]//ACM Sigmetrics BANFF,CA,2005:50-60.
  • 9FENG W,CHANG F,FENG W,et al.A traffic characterization of popular on-line games[J].IEEE/ACM Transactions on Networking,2005,13(3):488-500.

同被引文献24

  • 1程光,龚俭,丁伟,徐加羚.面向IP流测量的哈希算法研究[J].软件学报,2005,16(5):652-658. 被引量：54
  • 2SHULZRINNE H, CASNER S, FREDERICK R, et al. RFC3350, RTP: a transport protocol for real-time application [ S ]. [ S. 1. ] : In- temet Engineering Task Force, 2003.
  • 3李猛,施强,罗成,等.识剐非法分组电话用户的方法、装置及系统:中国,200610104253[P].2007-03-08.
  • 4ROUGHAN M, SEN S, SPATSCHECK O, et aL Class-of-service mapping for QoS: a statistical signature-based approach to IP traffic classification [ C]//Proc of ACM SIGCOMM Internet Measurement Conference. 2004 : 135-148.
  • 5ZANDER S, NGUYEN T, ARMITAGE G. Serf-learning IP traffic classification based on statistical flow characteristics[ C ]//Proc of the 6th Passive and Active Measurement Workshop. 2005:325-328.
  • 6McGREGOR A, HALL M, LORIER P, et al. Flow clustering using machine learning techniques [ C ]//Proc of the 5th Passive and Active Measurement Workshop ( PAM2004 ). 2004 : 205- 214.
  • 7DO L H, BRANCH P. Real time VoIP traffic classification, Techni- cal Report 090914AIR]. [S. 1. ] : CAIA, 2009.
  • 8WILLIAMS N, ZANDER S, ARMITAGE S G. A preliminary per- formance comparison of five machine learning algorithms for practical IP traffic flow classification [ C ]//Proc of ACM SIGCOMM Computer Communication Review. 2008:7-15.
  • 9NGUYEN T T T. A novel approach for practical real-time machine learning based IP traffic classification [ D ]. [ S. 1. ] : Swinbume Uni- vemity of Technology, 2009:271-273.
  • 10Calladoa A, Kelnerb J, Sadokb D, et al. Better Network Traffic Identification Through the Independent Combina- tion of Techniques[ J ]. Journal of Network and Com- puter Applications ,2010,33 (4) :433-446.

引证文献3

二级引证文献1

智能系统学报
2010年 第2期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部