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Related Experiment Videos

A multi-pattern hash-binary hybrid algorithm for URL matching in the HTTP protocol.

Ping Zeng1,2, Qingping Tan1,2, Xiankai Meng1

  • 1College of Computer, National University of Defense Technology, Changsha, Hunan, P.R. China.

Plos One
|April 12, 2017
PubMed
Summary
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We developed the MH algorithm, an improved multi-pattern matching method using hash and binary tables. This offers faster, memory-efficient string matching for network security and data analysis applications.

Area of Science:

  • Computer Science
  • Network Engineering
  • Data Science

Background:

  • Classical multi-pattern matching algorithms face performance limitations.
  • Efficient string matching is crucial for network security, data analysis, and communication systems.
  • Previous work introduced the HEM algorithm for uniform resource locator (URL) binary matching.

Purpose of the Study:

  • To propose an improved multi-pattern matching algorithm, MH, enhancing performance over existing methods.
  • To address the performance bottlenecks in classical string matching algorithms, particularly within the HTTP protocol.
  • To leverage hash and binary tables for efficient pattern matching from fixed starting positions.

Main Methods:

  • Developed the MH algorithm, combining hash tables and binary tables for multi-pattern matching.

Related Experiment Videos

  • Transformed symbol-space matching into digital-space numerical comparison and hashing.
  • Applied and evaluated the MH algorithm for string matching within HTTP streams.

    • Main Results:

    • The MH algorithm demonstrates significantly improved performance compared to classical algorithms and HEM.
    • Achieved fast matching speeds with minimal memory requirements.
    • Validated the algorithm's effectiveness in real-world application scenarios like network security and data analysis.

    Conclusions:

    • The MH algorithm offers a superior solution for multi-pattern string matching, especially in performance-critical applications.
    • Its efficiency and low memory footprint make it suitable for network security, data analysis, and cloud communications.
    • MH presents a promising advancement for optimizing string matching within HTTP traffic and related fields.