跟踪网络事件写优化的数据结构

Nolan Donoghue, B. Hahn, Helen Xu, Thomas M. Kroeger, David Zage, Rob Johnson
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引用次数: 2

摘要

访问网络流量记录是识别和解决网络安全漏洞的一个组成部分。即使网络攻击越来越复杂,基本的网络事件,如两个IP地址之间的连接,在任何网络防御中都扮演着重要的角色。鉴于当前攻击的持续时间,长期数据存档至关重要,但通常很少有数据被访问。以前的工作提供了工具并确定了跟踪连接的需要。然而,传统数据库会引起性能问题,因为它们是针对查询而不是摄取进行优化的。对写优化数据结构(WODS)的研究是一个新兴的领域,它为传统的存储结构(如b树)提供了一种新的方法。WODS以查询性能的轻微下降换取了快速插入更多数据元素的能力的显著提高,通常每秒插入次数增加10到100倍。这些高效的内存外数据结构可以在实现健壮的、长期的网络事件跟踪方面发挥关键作用。在本文中,我们提出TWIAD,写优化的IP地址数据库。TWIAD使用写优化的B树,即B树来跟踪网络流量流中的所有IP地址连接。我们最初的实现重点是利用低成本的硬件,证明基本的长期跟踪可以在没有先进设备的情况下完成。我们在一个普通的桌面系统上对TWIAD进行了测试,结果显示它的持续摄取速度约为每秒20,000次插入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tracking Network Events with Write Optimized Data Structures
Access to network traffic records is an integral part of recognizing and addressing network security breaches. Even with the increasing sophistication of network attacks, basic network events such as connections between two IP addresses play an important role in any network defense. Given the duration of current attacks, long-term data archival is critical but typically very little of the data is ever accessed. Previous work has provided tools and identified the need to trace connections. However, traditional databases raise performance concerns as they are optimized for querying rather than ingestion. The study of write-optimized data structures (WODS) is a new and growing field that provides a novel approach to traditional storage structures (e.g., B-trees). WODS trade minor degradations in query performance for significant gains in the ability to quickly insert more data elements, typically on the order of 10 to 100 times more inserts per second. These efficient, out-of-memory data structures can play a critical role in enabling robust, long-term tracking of network events. In this paper, we present TWIAD, the Write-optimized IP Address Database. TWIAD uses a write-optimized B-tree known as a B" tree to track all IP address connections in a network traffic stream. Our initial implementation focuses on utilizing lower cost hardware, demonstrating that basic long-term tracking can be done without advanced equipment. We tested TWIAD on a modest desktop system and showed a sustained ingestion rate of about 20,000 inserts per second.
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