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Exploiting Dynamicity in Graph-based Traffic Analysis: Techniques and Applications

机译:在基于图的流量分析中利用动态性:技术和应用

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Network traffic can be represented by a Traffic Dispersion Graph (TDG) that contains an edge between two nodes that send a particular type of traffic (e.g., DNS) to one another. TDGs have recently been proposed as an alternative way to interpret and visualize network traffic. Previous studies have focused on static properties of TDGs using graph snapshots in isolation. In this work, we represent network traffic with a series of related graph instances that change over time. This representation facilitates the analysis of the dynamic nature of network traffic, providing additional descriptive power. For example, DNS and P2P graph instances can appear similar when compared in isolation, but the way the DNS and P2P TDGs change over time differs significantly. To quantify the changes over time, we introduce a series of novel metrics that capture changes both in the graph structure (e.g., the average degree) and the participants (i.e., IP addresses) of a TDG. We apply our new methodologies to improve graph-based traffic classification and to detect changes in the profile of legacy applications (e.g., e-mail).
机译:网络流量可以由流量分散图(TDG)表示,该图包含两个节点之间的一条边,这两个节点之间可以相互发送特定类型的流量(例如DNS)。最近,已提出将TDG作为解释和可视化网络流量的替代方法。先前的研究集中在使用孤立的图形快照的TDG的静态属性上。在这项工作中,我们用一系列随时间变化的相关图实例来表示网络流量。这种表示方式有助于分析网络流量的动态性质,从而提供附加的描述能力。例如,当单独比较DNS和P2P图实例时,它们看起来可能相似,但是DNS和P2P TDG随时间变化的方式差异很大。为了量化随时间的变化,我们引入了一系列新颖的指标,可捕获TDG的图形结构(例如平均程度)和参与者(即IP地址)方面的变化。我们应用新的方法来改进基于图的流量分类,并检测传统应用程序(例如电子邮件)的配置文件中的更改。

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