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Offset-FA: A Uniform Method to Handle Both Unbounded and Bounded Repetitions in Regular Expression Matching.

Chengcheng Xu1, Kun Yu1, Xinghua Xu1

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Summary

Cyber-physical systems (CPSs) face security threats. This study introduces Offset-FA, a novel intrusion detection method that efficiently handles complex pattern repetitions, significantly improving space cost and matching speed for regular expression matching (REM).

Keywords:
CPS securitydeep-packet inspectionregular expression matchingstate explosion

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Area of Science:

  • Computer Science
  • Cybersecurity
  • Network Security

Background:

  • Cyber-physical systems (CPSs) are increasingly vulnerable to attacks, necessitating robust intrusion detection.
  • Deep-packet inspection using regular expression matching (REM) is crucial for identifying threats in network traffic.
  • State explosion in REM, caused by repetitive patterns, poses a significant challenge to efficient threat detection.

Purpose of the Study:

  • To propose Offset-FA, a novel automaton designed to uniformly handle bounded and unbounded repetitions in REM.
  • To address the state explosion problem in REM for enhanced CPS security.
  • To improve the efficiency of intrusion detection mechanisms in CPS environments.

Main Methods:

  • Offset-FA extracts repetitive elements from strings, compiling them into a fragment-DFA.
  • It utilizes a fragment relation table and a reset table to maintain connections and offsets.
  • This approach uniformly manages both bounded (counting) and unbounded (closures) repetitions.

Main Results:

  • Offset-FA effectively eliminates state explosion by managing repetitions within string fragments.
  • Experiments show Offset-FA significantly outperforms existing solutions in space cost and matching speed.
  • The proposed method achieves matching speeds comparable to DFA on practical rule sets while ensuring correctness.

Conclusions:

  • Offset-FA provides a unified mechanism for handling complex repetitions in REM, overcoming state explosion.
  • This advancement offers a more efficient and effective solution for intrusion detection in CPS.
  • The method demonstrates superior performance in space efficiency and detection speed for network security applications.