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A real-time identification system of unstructured P2P multicast video streaming

机译:非结构化P2P多播视频流的实时识别系统

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The identification of unstructured P2P multicast video streaming is the premise for playing online linkage and real-time evidence in the process of network monitoring management. Based on our preliminary research, a real-time identification system is designed and implemented. The system selects flow features and behavior features which are more real-time and have stronger distinction, adopts the machine learning method of support vector machines, and then successively separates the network traffic until the applications of unstructured P2P multicast video streaming are identified. The system can adapt to the changing network and identify known and unknown applications. Besides, in order to make the network managers recognize and block up the abnormal unstructured P2P multicast video streaming in time, it also has the advantages of strong real-time and low computational complexity.
机译:非结构化P2P组播视频流的识别是在网络监控管理过程中播放在线联动和实时证据的前提。根据我们的初步研究,设计和实施了实时识别系统。该系统选择更实时的流特征和行为特征,并且具有更强的区别,采用支持向量机的机器学习方法,然后连续地将网络流量分开,直到识别非结构化P2P组播视频流的应用。系统可以适应更改网络并识别已知和未知的应用程序。此外,为了使网络管理者能够及时识别并阻止异常非结构化的P2P组播视频流,它还具有强大的实时和低计算复杂性的优点。

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