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Optimized Parallel Aho-Corasick Algorithm on GPU

Publication Date : 10/07/2015

Author(s) :

Prachi S. Oke , Mrs. Archana S. Vaidya.

Conference Name :
4th International Conference on Recent Trends in Engineering & Technology(ICRTET-2015) July 2-4,2015 Organized by SNJB's KBJ College of Engineering,Chandwad,Nashik,Maharashtra,India

Abstract :

Network Intrusion Detection Systems (NIDS) need to handle very computationally intensive operations like pattern matching, where huge amount of data needs to be matched against the known patterns. Storage capacity and link speed has increased with the advent in technology. Therefore there has been an increase in the amount of data that needs to be matched against the known patterns. The traditional algorithms cannot handle this increased amount of data. Therefore, we need such a hardware and software solution that would help to handle this increased amount of incoming data in NIDS to match it with the known patterns. We are using parallel multipattern matching algorithm that matches an input string with the known patterns (attack patterns or virus signatures) to check for the presence of any pattern in an input string and it would return the same if any. We are running this algorithm on NVIDIA Geforce GTX 680 GPU with CUDA 6.5 programming model. We have also introduced several optimization techniques for the Parallel AC algorithm that would result in the reduction of memory usage, time and cost required to execute Parallel AC algorithm on GPU.

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