A pattern group partitioning for parallel string matching using a pattern grouping metric

Hyunjin Kim, Sungho Kang

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Considering the increasing number of target patterns for the intrusion detection systems (IDS), memory requirements should be minimized for reducing hardware overhead. This paper proposes an algorithm that partitions a set of target patterns into multiple subgroups for homogeneous string matchers. Using a pattern grouping metric, the proposed pattern partitioning makes the average length of the mapped target patterns onto a string matcher approximately equal to the average length of total target patterns. Therefore, the variety of target pattern lengths can be mitigated because the number of mapped target patterns onto each string matcher is balanced.

Original languageEnglish
Article number5547596
Pages (from-to)878-880
Number of pages3
JournalIEEE Communications Letters
Volume14
Issue number9
DOIs
Publication statusPublished - 2010 Sep 1

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering

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