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Exploring efficient grouping algorithms in regular expression matching.

Chengcheng Xu1, Jinshu Su1,2, Shuhui Chen1

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This summary is machine-generated.

This study introduces an efficient rule grouping method to address the state explosion problem in deterministic finite automata (DFA) for regular expression matching (REM). The proposed one-step greedy (OSG) algorithm significantly reduces DFA states and grouping time, outperforming existing solutions.

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Area of Science:

  • Computer Science
  • Algorithm Design
  • Network Security

Background:

  • Regular expression matching (REM) is crucial for deep packet inspection (DPI).
  • Converting patterns to deterministic finite automata (DFA) faces state explosion challenges with complex rule sets.
  • Rule grouping offers a solution by dividing rules into smaller DFAs.

Purpose of the Study:

  • To develop an efficient rule grouping method for REM.
  • Minimize the total number of DFA states for efficient memory deployment.
  • Reduce the time cost associated with pattern grouping and updates.

Main Methods:

  • Quantified rule interactions to frame grouping as a maximum k-cut graph partitioning problem.
  • Proposed the one-step greedy (OSG) algorithm, a heuristic approach for the NP-hard problem.
  • Devised a heuristic initialization (HI) subroutine to further optimize grouping.

Main Results:

  • The OSG algorithm demonstrated superior performance over state-of-the-art methods.
  • Achieved significant reductions in both total DFA states and grouping time.
  • The HI subroutine effectively enhanced the optimization of grouping algorithms.

Conclusions:

  • The proposed compact and efficient grouping algorithm effectively tackles DFA state explosion in REM.
  • Experimental results on practical rule sets confirm the superiority of the OSG and HI approach.
  • This method provides a practical solution for efficient and scalable deep packet inspection.