网络入侵检测系统的高效多模式匹配算法

Sunho Lee, Dong Kyue Kim
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引用次数: 1

摘要

多种模式匹配算法是网络入侵检测系统(nids)检测数据包是否存在恶意模式的关键引擎。对于一组模式,多模式匹配算法通常构建一个trie数据结构。在本文中,我们提出了一种基于线性化紧树的多模式匹配算法的高效实现方法。这个线性化的紧凑trie是紧凑trie的数组表示,它保证大小与模式的数量成线性关系,查找时间损失很小。因此,我们的实现在短时间内实现了紧凑的大小,因此对硬件嵌入和缓存利用很有用。
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Efficient multiple pattern matching algorithms for Network Intrusion Detection Systems
Multiple pattern matching algorithms are essential engines of Network Intrusion Detection Systems (NIDSs) to inspect packets for occurrences of malicious patterns. For a set of patterns, the multiple pattern matching algorithms usually build a trie data structure. In this paper, we propose efficient implementations of the multiple pattern matching algorithms widely used in NIDSs by using a linearized compact trie. This linearized compact trie is an array representation of a compact trie and guarantees a size linear to the number of patterns with little loss of lookup time. Thus, our implementations achieve compact sizes with fast time, so it is useful to hardware embedding and cache exploiting.
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