Length-bounded hybrid CPU/GPU pattern matching algorithm for deep packet inspection

Yi Shan Lin, Chun Liang Lee*, Yaw-Chung Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Since frequent communication between applications takes place in high speed networks, deep packet inspection (DPI) plays an important role in the network application awareness. The signature-based network intrusion detection system (NIDS) contains a DPI technique that examines the incoming packet payloads by employing a pattern matching algorithm that dominates the overall inspection performance. Existing studies focused on implementing efficient pattern matching algorithms by parallel programming on software platforms because of the advantages of lower cost and higher scalability. Either the central processing unit (CPU) or the graphic processing unit (GPU) were involved. Our studies focused on designing a pattern matching algorithm based on the cooperation between both CPU and GPU. In this paper, we present an enhanced design for our previous work, a length-bounded hybrid CPU/GPU pattern matching algorithm (LHPMA). In the preliminary experiment, the performance and comparison with the previous work are displayed, and the experimental results show that the LHPMA can achieve not only effective CPU/GPU cooperation but also higher throughput than the previous method.

Original languageEnglish
Article number16
JournalAlgorithms
Volume10
Issue number1
DOIs
StatePublished - 1 Jan 2017

Keywords

  • Compute unified device architecture
  • Deep packet inspection
  • General-purpose graphics processing unit
  • Intrusion detection system
  • Network security
  • Pattern matching algorithm

Fingerprint Dive into the research topics of 'Length-bounded hybrid CPU/GPU pattern matching algorithm for deep packet inspection'. Together they form a unique fingerprint.

Cite this