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22nd Annual Computer Security Applications Conference (ACSAC'06)
Offloading IDS Computation to the GPU
Miami Beach, Florida, USA
December 11-December 15
ISBN: 0-7695-2716-7
Nigel Jacob, Tufts University, USA
Carla Brodley, Tufts University, USA
Signature-matching Intrusion Detection Systems can experience significant decreases in performance when the load on the IDS-host increases. We propose a solution that off-loads some of the computation performed by the IDS to the Graphics Processing Unit (GPU). Modern GPUs are programmable, stream-processors capable of high-performance computing that in recent years have been used in non-graphical computing tasks. The major operation in a signature-matching IDS is matching values seen operation to known black-listed values, as such, our solution implements the string-matching on the GPU. The results show that as the CPU load on the IDS host system increases, PixelSnort?s performance is significantly more robust and is able to outperform conventional Snort by up to 40%.
Citation:
Nigel Jacob, Carla Brodley, "Offloading IDS Computation to the GPU," acsac, pp.371-380, 22nd Annual Computer Security Applications Conference (ACSAC'06), 2006
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