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A High-Speed Network Data Acquisition System Based on Big Data Platform

机译:基于大数据平台的高速网络数据采集系统

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摘要

This paper designs a high-speed network data acquisition system based on big data platform with good expansibility and high real-time, aiming at the need of enterprises or organizations to acquire high-speed network data efficiently in network intrusion detection. Taking into account the storage capacity and computing power requirements of high-speed network traffic capture and processing, the whole system is divided into two parts. The front-end adopts high-performance network traffic distributor based on hardware, and uses it to divide the high-speed network traffic into multiple low-speed branch traffic. The back-end data acquisition and processing system is implemented by clustering of normal PC, and the software system is optimized by introducing big data technology. The use of distributed storage and computing improve data processing performance. The system acquires the complete network data through distribution, capture, cache, layered protocol analysis, session reassembly, application layer data extraction and so on, which can provide reference for intrusion detection.
机译:针对企业或组织在网络入侵检测中有效地获取高速网络数据的需求,设计了一种基于大数据平台的,具有良好扩展性和实时性的高速网络数据获取系统。考虑到高速网络流量捕获和处理的存储容量和计算能力要求,整个系统分为两部分。前端采用基于硬件的高性能网络流量分配器,并使用它将高速网络流量划分为多个低速分支流量。后端数据采集与处理系统是通过普通PC机的集群来实现的,软件系统是通过引入大数据技术来进行优化的。分布式存储和计算的使用提高了数据处理性能。该系统通过分布,捕获,缓存,分层协议分析,会话重组,应用层数据提取等方式获取完整的网络数据,可为入侵检测提供参考。

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