Research Article

A Cache Oblivious based GA Solution for Clustering Problem in IDS

by  Vignesh R, Ganesh B, Aarthi G, Iyswarya N
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Issue 11
Published: February 2010
Authors: Vignesh R, Ganesh B, Aarthi G, Iyswarya N
10.5120/235-389
PDF

Vignesh R, Ganesh B, Aarthi G, Iyswarya N . A Cache Oblivious based GA Solution for Clustering Problem in IDS. International Journal of Computer Applications. 1, 11 (February 2010), 82-86. DOI=10.5120/235-389

                        @article{ 10.5120/235-389,
                        author  = { Vignesh R,Ganesh B,Aarthi G,Iyswarya N },
                        title   = { A Cache Oblivious based GA Solution for Clustering Problem in IDS },
                        journal = { International Journal of Computer Applications },
                        year    = { 2010 },
                        volume  = { 1 },
                        number  = { 11 },
                        pages   = { 82-86 },
                        doi     = { 10.5120/235-389 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2010
                        %A Vignesh R
                        %A Ganesh B
                        %A Aarthi G
                        %A Iyswarya N
                        %T A Cache Oblivious based GA Solution for Clustering Problem in IDS%T 
                        %J International Journal of Computer Applications
                        %V 1
                        %N 11
                        %P 82-86
                        %R 10.5120/235-389
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

In this we present an efficient solution for eliminating false positives in intrusion detection systems using a parallelized version of Genetic Algorithm. Genetic algorithm uses selection, mutation and crossover operations eliminating most of the false positives in a reasonable time. Almost all existing versions are sequential without exploiting the capabilities of newer multiprocessors or distributed systems. By parallelizing genetic operations in the context of intrusion detection systems we reduce the total complexities. This parallelized approach gives better solution than sequential one by taking advantage of the parallel architecture. We propose the use of cache oblivious technique in our algorithm to provide efficient memory transfers. The complexity of this algorithm is O((N/B) logM/B N1/3/3 + N1/ 3) which is very much lesser when compared to other sorting algorithms.

References
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Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Cache Oblivious Clustering Genetic algorithm False Positive Funnel Sort

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