Performance comparison and optimization of mainstream NIDS systems in offline mode based on parallel processing technology

Tianyang Zhou
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Abstract

For the network intrusion detection system (NIDS), improving the performance of the analysis process has always been one of the primary goals that NIDS needs to solve. An important method to improve performance is to use parallel processing technology to maximize the usage of multi-core CPU resources. In this paper, by splitting Pcap data packets, the NIDS software Snort3 can process Pcap packets in parallel mode. On this basis, this paper compares the performance between Snort2, Suricata, and Snort3 with different CPU cores in processing different sizes of Pcap data packets. At the same time, a parallel unpacking algorithm is proposed to further improve the parallel processing performance of Snort3.
基于并行处理技术的主流网络入侵检测系统离线模式性能比较与优化
对于网络入侵检测系统(NIDS)来说,提高分析过程的性能一直是NIDS需要解决的主要目标之一。利用并行处理技术最大限度地利用多核CPU资源是提高性能的一个重要方法。在本文中,通过拆分Pcap数据包,NIDS软件Snort3可以以并行模式处理Pcap数据包。在此基础上,本文比较了不同CPU核的Snort2、Suricata和Snort3处理不同大小Pcap数据包的性能。同时,为了进一步提高Snort3的并行处理性能,提出了一种并行解包算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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