Implementation of Multipattern String Matching Accelerated with GPU for Intrusion Detection System

Abstract. As Internet-related  security threats continue to increase  in terms of volume and sophistication,  existing  Intrusion Detection System  is also  being challenged to cope with the current Internet  development. Multi Pattern String Matching algorithm accelerated with Graphical  Processing Unit  is  being  utilized  to improve  the packet scanning performance  of the  IDS. This paper implements a Multi Pattern String Matching algorithm, also called Parallel Failureless Aho  Corasick  accelerated with  GPU to  improve the  performance of IDS.  OpenCL library  is  used  to  allow  the  IDS  to  support  various GPU, including  popular GPU such  as NVIDIA and AMD, used  in our research. The  experiment result  shows that the application of Multi  Pattern String Matching using GPU  accelerated platform provides  a speed up,  by up  to 141% in term of throughput compared to the  previous  research

Parallel Implementation of the Wu-Manber Algorithm Using the OpenCL Framework

Part 8: First Workshop on Algorithms for Data and Text Mining in Bioinformatics (WADTMB 2012)International audienceOne of the most significant issues of the computational biology is the multiple pattern matching for locating nucleotides and amino acid sequence patterns into biological databases. Sequential implementations for these processes have become inadequate, due to an increasing demand for more computational power. Graphic cards offer a high parallelism computational power improving the performance of applications. This paper evaluates the performance of the Wu-Manber algorithm implemented with the OpenCL framework, by presenting the running time of the experiments compared with the corresponding sequential time