Multiple Pattern Matching for Network Security Applications: Acceleration through Vectorization
Paper in proceeding, 2017

Pattern matching is a key building block of Intrusion Detection Systems and firewalls, which are deployed nowadays on commodity systems from laptops to massive web servers in the cloud. In fact, pattern matching is one of their most computationally intensive parts and a bottleneck to their performance. In Network Intrusion Detection, for example, pattern matching algorithms handle thousands of patterns and contribute to more than 70% of the total running time of the system.In this paper, we introduce efficient algorithmic designs for multiple pattern matching which (a) ensure cache locality and (b) utilize modern SIMD instructions. We first identify properties of pattern matching that make it fit for vectorization and show how to use them in the algorithmic design. Second, we build on an earlier, cache-aware algorithmic design and we show how cache-locality combined with SIMD gather instructions, introduced in 2013 to Intel's family of processors, can be applied to pattern matching. We evaluate our algorithmic design with open data sets of real-world network traffic:Our results on two different platforms, Haswell and Xeon-Phi, show a speedup of 1.8x and 3.6x, respectively, over Direct Filter Classification (DFC), a recently proposed algorithm by Choi et al. for pattern matching exploiting cache locality, and a speedup of more than 2.3x over Aho-Corasick, a widely used algorithm in today's Intrusion Detection Systems.

Hardware

Pattern matching

Data structures

Algorithm design and analysis

vectors

SIMD instructions

network security applications

intrusion detection systems

pattern matching

Registers

SIMD vectorization

gather

cache locality

cache-aware algorithmic design

Intrusion detection

vectorization

cache storage

Program processors

firewalls

Author

Charalampos Stylianopoulos

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Magnus Almgren

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Olaf Landsiedel

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Marina Papatriantafilou

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

46th International Conference on Parallel Processing, ICPP 2017

472-482
978-1-5386-1042-8 (ISBN)

46th International Conference on Parallel Processing (ICPP)
Bristol, ,

Resilient Information and Control Systems (RICS)

Swedish Civil Contingencies Agency (2015-828), 2015-09-01 -- 2020-08-31.

Subject Categories

Computer Engineering

Computer Science

Computer Systems

DOI

10.1109/ICPP.2017.56

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Latest update

4/1/2020 1