Offset-FA: Detach the Closures and Countings for Efficient Regular Expression Matching

Chengcheng Xu, Jinshu Su, Shuhui Chen, Biao Han
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引用次数: 2

Abstract

Fast regular expression matching (REM) is the core issue in deep packet inspection (DPI). Traditional REM mainly relies on deterministic finite automaton (DFA) to achieve fast matching. However, state explosion usually makes the DFA infeasible in practice. We propose the offset-FA to solve the state explosion problem in REM. The state explosion is mainly caused by the features of the large character set with closures or counting repetitions. We extract these features from original patterns, and represent them as an offset relation table and a reset table to keep semantic equivalence, and the rest fragments are compiled to a DFA called fragment-DFA. The fragment-DFA along with the offset relation table and reset table compose our Offset-FA. Experiments show that the offset-FA supports large rule sets and outperforms state-of-the-art solutions in space cost and matching speed.
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Offset-FA:分离闭包和计数以实现有效的正则表达式匹配
快速正则表达式匹配(REM)是深度包检测的核心问题。传统的快速匹配算法主要依靠确定性有限自动机(DFA)来实现快速匹配。然而,由于状态爆炸的原因,DFA在实际应用中往往不可行。为了解决REM中的状态爆炸问题,我们提出了偏移fa。状态爆炸主要是由带有闭包或计数重复的大字符集的特征引起的。我们从原始模式中提取这些特征,并将其表示为偏移关系表和重置表,以保持语义等价,其余的片段被编译成一个DFA,称为片段-DFA。片段- dfa与偏移关系表和重置表一起构成偏移- fa。实验表明,偏移fa支持大型规则集,并且在空间成本和匹配速度方面优于最先进的解决方案。
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