Characterizing sources and remedies for packet loss in network intrusion detection systems

Lambert Schaelicke, J. C. Freeland
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引用次数: 22

Abstract

Network intrusion detection is becoming an increasingly important tool to protect critical information and infrastructure from unauthorized access. Network intrusion detection systems (NIDS) are commonly based on general-purpose workstations connected to a network tap. However, these general-purpose systems, although cost-efficient, are not able to sustain the packet rates of modern high-speed networks. The resulting packet loss degrades the system's overall effectiveness, since attackers can intentionally overload the NIDS to evade detection. This paper studies the performance requirements of a commonly used open-source NIDS on a modern workstation architecture. Using full-system simulation, this paper characterizes the impact of a number of system-level optimizations and architectural trends on packet loss, and highlights the key bottlenecks for this type of network-intensive workloads. Results suggest that interrupt aggregation combined with rule set pruning is most effective in minimizing packet loss. Surprisingly, the workload also exhibits sufficient locality to benefit from larger level-2 caches as well. On the other hand, many other common architecture and system optimizations have only a negligible impact on throughput.
描述网络入侵检测系统中丢包的来源和补救措施
网络入侵检测已成为保护关键信息和基础设施免遭未经授权访问的重要工具。网络入侵检测系统(NIDS)通常基于连接到网络抽头的通用工作站。然而,这些通用的系统,虽然成本效益高,却不能维持现代高速网络的分组速率。由于攻击者可以故意使NIDS过载以逃避检测,因此导致的数据包丢失会降低系统的整体效率。本文研究了一种常用的开源NIDS在现代工作站架构下的性能需求。使用全系统模拟,本文描述了许多系统级优化和体系结构趋势对数据包丢失的影响,并强调了这种类型的网络密集型工作负载的关键瓶颈。结果表明,中断聚合与规则集修剪相结合在减少丢包方面是最有效的。令人惊讶的是,工作负载还显示出足够的局部性,从而从更大的2级缓存中获益。另一方面,许多其他常见的架构和系统优化对吞吐量的影响可以忽略不计。
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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