基于NetFlow的IP网络行为分析系统的设计与实现

H. Hou, Tongge Xu, R. Zou
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引用次数: 1

摘要

互联网的高速发展对网络管理提出了巨大的挑战。更大的网络流量和更复杂的应用使得原有的基于snmp的网络管理软件难以满足用户和协议分析的需求;动态端口的广泛使用大大降低了基于传统静态端口区分应用层协议的准确性。由于原始NetFlow数据量大,不适合长期存储,查询效率低,设计了多时间粒度聚合方案。本文从五个方面描述了实时流量和历史流量的特点,从而对网络运行状况有了更清晰的认识。此外,网站和url作为用户网络访问行为的指标进行了分析。
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Design and implementation of IP network behaviour analysis system based on NetFlow
The high-speed development of the Internet has brought up a huge challenge for network management. Larger network traffic and more complex applications make it difficult for the original SNMP-based network management software to meet demands of analyzing users and protocols; widespread utility of dynamic ports greatly reduces the accuracy of distinguishing application layer protocols based on tranditional static ports. Since raw NetFlow is enormous, unfit for long-term storage and low in query efficiency, multiple time granularity aggregation schemes are designed. This paper describes characteristics of both real-time and history traffic from five aspects, thus providing a clearer view of network operating conditions. Besides, as the indicator of users' web access behavior, web sites and URLs are analyzed.
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