Hybridized Intrusion Detection System Using Genetic and Tabu Search Algorithm

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dc.contributor.authorAbikoye, Oluwakemi Christiana
dc.contributor.authorAro, Taye Oladele
dc.contributor.authorObisesan, Racheal Oyeranti
dc.contributor.authorBabatunde, Akinbowale Nathaniel
dc.date.accessioned2018-03-21T10:11:17Z
dc.date.available2018-03-21T10:11:17Z
dc.date.issued2017
dc.description.abstractAs transactions, data communication and information systems are drastically increasing in the society, so many people are connected through internet for e-commerce and other electronic activities. The introduction of internet technology in business brings about great relief in reaching the end users. Also this technology invites numerous security threats of misuses and intrusions. Intrusion detection systems are significant element for network security infrastructure which plays key role in the detection of several attacks along the network. They are several techniques being employed in intrusion detection, but these methods are not completely flawless. In quest for an efficient Intrusion Detection System (IDS), this study employs hybridization technique which involves the Genetic Algorithm and Tabu-search to produce a robust Intrusion Detection System. Evaluation of the system on KKD 99 intrusion database, shows that the performance of proposed hybridized IDS is better than that of Genetic algorithm or tabu search method alone which can significantly detect almost all anomaly data in the computer network.en_US
dc.identifier.citationAbikoye, Oluwakemi Christiana., Aro, Taye Oladele, Obisesan, Rachael Oyeranti & Babatunde, Akinbowale Nathaniel. (2017): Hybridized Intrusion Detection System Using Genetic and Tabu Search Algorithm. Anale. Seria Informatică( Annals. Computer Science Series ). 15(1); 139-150, Published by Faculty of Computers and Applied Computer Science, "Tibiscus" University of Timişoara, Romania.en_US
dc.identifier.urihttp://www.anale-informatica.tibiscus.ro/download/lucrari/15-1-17-Abikoye.pdf
dc.identifier.urihttp://hdl.handle.net/123456789/138
dc.language.isoenen_US
dc.publisherFaculty of Computers and Applied Computer Science, "Tibiscus" University of Timişoara, Romania.en_US
dc.subjectTabu Searchen_US
dc.subjectElectronic Transaction.en_US
dc.subjectInformation Systemen_US
dc.subjectdata communicationen_US
dc.subjectIntrusion detectionen_US
dc.subjectGenetic Algorithmen_US
dc.titleHybridized Intrusion Detection System Using Genetic and Tabu Search Algorithmen_US
dc.typeArticleen_US

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