Identifying Skype Traffic in a Large-Scale Flow Data Repository

机译：在大型流数据存储库中识别Skype流量

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We present a novel method for identifying Skype clients and supernodes on a network using only flow data, based upon the detection of certain Skype control traffic. Flow-level identification allows long-term retrospective studies of Skype traffic as well as studies of Skype traffic on much larger scale networks than existing packet-based approaches. We use this method to identify Skype hosts and connection events to the network in a historical flow data set containing 182 full days of data over the six years from 2004 to 2009, in order to explore the evolution of the Skype network in general and a large observed portion thereof in particular. This represents, to the best of our knowledge, the first long-term retrospective analysis of the behavior of the Skype network based solely on flow data, and the first successful application of a Skype detection algorithm to flow data collected from a production network.

机译：我们基于对某些Skype控制流量的检测，提出了一种仅使用流数据识别网络上的Skype客户端和超节点的新颖方法。流量级别识别允许对Skype流量进行长期的回顾性研究，以及比现有的基于数据包的方法在更大规模的网络上对Skype流量进行研究。我们使用这种方法在历史流量数据集中识别Skype主机和到网络的连接事件，该数据集中包含从2004年到2009年的6年中182天的数据，目的是探讨Skype网络的总体发展情况特别是观察到的部分。据我们所知，这是首次仅基于流数据对Skype网络的行为进行的长期回顾性分析，并且是Skype检测算法首次成功应用于从生产网络收集的流数据的分析。

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来源
《Traffic monitoring and analysis》|2011年|p.72-85|共14页
会议地点 Vienna(AT);Vienna(AT)
作者
Brian Trammell; Elisa Boschi; Gregorio Procissi; Christian Callegari; Peter Dorfinger; Dominik Schatzmann;
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作者单位

ETH Zurich, Zurich, Switzerland;

ETH Zurich, Zurich, Switzerland;

Universita di Pisa, Pisa, Italy;

Universita di Pisa, Pisa, Italy;

Salzburg Research, Salzburg, Austria;

ETH Zurich, Zurich, Switzerland;

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原文格式 PDF
正文语种 eng
中图分类计算机网络;
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专利

1. On Metrics to Distinguish Skype Flows from HTTP Traffic [J] . Emanuel Pacheco Freire, Artur Ziviani, Ronaldo Moreira Salles Journal of network and systems management . 2009,第1a2期

机译：关于区分HTTP流量中的Skype流的度量标准
2. CIPRO 2.5: Ciona intestinalis protein database, a unique integrated repository of large-scale omics data, bioinformatic analyses and curated annotation, with user rating and reviewing functionality [J] . Akiyasu C. Yoshizawa, Ayako Nakajima, Chisato Yamasaki, Nucleic acids research . 2011,第suppla1期

机译：CIPRO 2.5：Ciona小肠蛋白质数据库，一个独特的集成的大型数据库，包括大型组学数据，生物信息学分析和精选注释，具有用户评分和查看功能
3. CIPRO 2.5:?Ciona intestinalis?Protein Database - a unique integrated repository of large-scale omics data, bioinformatic analyses, and curated annotation, with ability for user rating and comments [J] . Toshinori Endo, ?Keisuke Ueno, ?Kouki Yonezawa, Genome Biology . 2010,第Suppla1期

机译：Cipro 2.5：？Ciona Intestinalis？蛋白质数据库 - 一种独特的大规模OMIC数据，生物信息分析和策划注释的独特集成储存，具有用户评级和评论的能力
4. Machine learning based encrypted traffic classification: Identifying SSH and Skype [C] . Alshammari Riyad, Zincir-Heywood A. Nur IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA 2009) . 2009

机译：基于机器学习的加密流量分类：识别SSH和Skype
5. Efficient algorithms for querying large-scale data in relational, XML, and graph-structured data repositories. [D] . Gou, Gang. 2008

机译：在关系，XML和图结构数据存储库中查询大型数据的高效算法。
6. CIPRO 2.5: Ciona intestinalis protein database a unique integrated repository of large-scale omics data bioinformatic analyses and curated annotation with user rating and reviewing functionality [O] . Toshinori Endo, Keisuke Ueno, Kouki Yonezawa, 2011

机译：CIPRO 2.5：Ciona小肠蛋白质数据库一个独特的集成的大型数据库包括大型组学数据生物信息学分析和精选注释具有用户评分和审阅功能
7. Identifying Skype Traffic Using NetFlow Data [O] . Šebeň Patrik 2012

机译：使用NetFlow数据识别Skype流量

Identifying Skype Traffic in a Large-Scale Flow Data Repository

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