Picking pesky parameters: optimizing regular expression matching in practice

  • Authors:
  • Xinming Chen;Brandon Jones;Michela Becchi;Tilman Wolf

  • Affiliations:
  • University of Massachusetts, Amherst, Amherst, MA, USA;University of Missouri, Columbia, MO, USA;University of Missouri, Columbia, MO, USA;University of Massachusetts, Amherst, Amherst, MA, USA

  • Venue:
  • ANCS '13 Proceedings of the ninth ACM/IEEE symposium on Architectures for networking and communications systems
  • Year:
  • 2013

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Abstract

Network security systems inspect packet payloads for signatures of attacks. These systems use regular expression matching at their core. Many techniques for implementing regular expression matching at line rate have been proposed. Solutions differ in the type of automaton used (i.e., deterministic vs. non-deterministic) and in the configuration of implementation-specific parameters. While each solution has been shown to perform well on specific rule sets and traffic patterns, there has been no systematic comparison across a large set of solutions, rule sets and traffic patterns. Thus, it is extremely challenging for a practitioner to make an informed decision within the plethora of existing algorithmic and architectural proposals. To address this problem, we present a comprehensive evaluation of a broad set of regular expression matching techniques. We consider both algorithmic and architectural aspects. Specifically, we explore the performance, area requirements, and power consumption of implementations targeting processors and field programmable gate arrays using rule sets of practical size and complexity. We present detailed performance results and specific guidelines for determining optimal configurations based on a simple evaluation of the rule set. These guidelines can help significantly when implementing regular expression matching systems in practice.