Abikoye, Oluwakemi ChristianaAro, Taye OladeleObisesan, Racheal OyerantiBabatunde, Akinbowale Nathaniel2018-03-212018-03-212017Abikoye, 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.http://www.anale-informatica.tibiscus.ro/download/lucrari/15-1-17-Abikoye.pdfhttp://hdl.handle.net/123456789/138As 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.enTabu SearchElectronic Transaction.Information Systemdata communicationIntrusion detectionGenetic AlgorithmArticle