A highly-efficient memory-compression scheme for GPU-accelerated intrusion detection systems

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

7 Citations (Scopus)

Abstract

Pattern Matching is a computationally intensive task used in many research fields and real world applications. Due to the ever-growing volume of data to be processed, and increasing link speeds, the number of patterns to be matched has risen significantly. In this paper we explore the parallel capabilities of modern General Purpose Graphics Processing Units (GPGPU) applications for high speed pattern matching. A highly compressed failure-less Aho-Corasick algorithm is presented for Intrusion Detection Systems on off-the-shelf hardware. This approach maximises the bandwidth for data transfers between the host and the Graphics Processing Unit (GPU). Experiments are performed on multiple alphabet sizes, demonstrating the capabilities of the library to be used in different research fields, while sustaining an adequate throughput for intrusion detection systems or DNA sequencing. The work also explores the performance impact of adequate prefix matching for alphabet sizes and varying pattern numbers achieving speeds up to 8Gbps and low memory consumption for intrusion detection systems.
Original languageEnglish
Title of host publicationSIN '14 Proceedings of the 7th International Conference on Security of Information and Networks
Place of PublicationNew York
DOIs
Publication statusPublished - Sep 2014
Event7th International Conference on the Security of Information and Networks (SIN14) - University of Glasgow, Glasgow, United Kingdom
Duration: 9 Sep 201411 Sep 2014

Conference

Conference7th International Conference on the Security of Information and Networks (SIN14)
CountryUnited Kingdom
CityGlasgow
Period9/09/1411/09/14

Keywords

  • pattern matching
  • high speed pattern matching
  • Aho-Corasick algorithm
  • information networks

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