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Optimizations of Flow-based Behavior Recognition System within Hi-speed Network

机译:高速网络中基于流的行为识别系统的优化

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摘要

Since the endless new networking applications and security issues, it's urgent for governments, corporations and ISPs to identify, classify and control the network flows. Comparing with DPI technologies, flow-based behavior recognition has advantages of continuity and extensibility, but has the problems of scalability, efficiency and coordination which greatly restrict its implementation in high-speed core network. Base on related research and experiments, this paper presents optimizations to improve the performance of time and space of flow-based behavior recognition.
机译:由于无休止的新网络应用和安全问题,政府,企业和ISP迫切需要识别,分类和控制网络流量。与DPI技术相比,基于流的行为识别具有连续性和可扩展性的优点,但是具有可扩展性,效率和协调性的问题,这极大地限制了其在高速核心网中的实现。在相关研究和实验的基础上,本文提出了优化措施,以改进基于流的行为识别的时间和空间性能。

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