高速网络中基于流量的行为识别系统优化

Peng Xiaotian
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引用次数: 1

摘要

由于层出不穷的新网络应用和安全问题,政府、企业和互联网服务提供商迫切需要对网络流量进行识别、分类和控制。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,但存在可扩展性、效率和协调性等问题,严重制约了其在高速核心网中的实现。在相关研究和实验的基础上,对基于流的行为识别进行了优化,提高了识别的时间和空间性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimizations of Flow-based Behavior Recognition System within Hi-speed Network
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.
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