Efficient pattern matching on GPUs for intrusion detection systems

Abstract

In this paper we present an efficient implementation of the Aho-Corasick pattern matching algorithm on Graphics Processing Units (GPU), showing how we redesigned the algorithm and the data structures to fit on the architecture and comparing it with an equivalent implementation on the CPU. We show that with a synthetic dataset, our implementation obtains a speedup up to 6.67 with respect to the CPU solution.