Date on Master's Thesis/Doctoral Dissertation
5-2012
Document Type
Master's Thesis
Degree Name
M.S.
Department
Computer Engineering and Computer Science
Committee Chair
Ouyang, Ming
Author's Keywords
GPU parallel programming; Parallel NIDS; CUDA; NIDS GPU; Snort GPU; CUDA NIDS GPU
Subject
Computer networks--Security measures
Abstract
As network speeds continue to increase and attacks get increasingly more complicated, there is need to improved detection algorithms and improved performance of Network Intrusion Detection Systems (NIDS). Recently, several attempts have been made to use the underutilized parallel processing capabilities of GPUs, to offload the costly NIDS pattern matching algorithms. This thesis presents an interface for NIDS Snort that allows porting of the pattern-matching algorithm to run on a GPU. The analysis show that this system can achieve up to four times speedup over the existing Snort implementation and that GPUs can be effectively utilized to perform intensive computational processes like pattern matching.
Recommended Citation
Madhusoodhanan Sathik, Anju Panicker 1984-, "Parallelizing a network intrusion detection system using a GPU." (2012). Electronic Theses and Dissertations. Paper 879.
https://doi.org/10.18297/etd/879
