Intrusion Detection Systems using Data Mining Techniques: A comparative study

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dc.contributor.authorHaddadi, Mohamed
dc.contributor.authorKhiat, Abdelhamid
dc.contributor.authorBahnes, Nacera
dc.date.accessioned2024-02-27T10:05:41Z
dc.date.available2024-02-27T10:05:41Z
dc.date.issued2022-01-20
dc.description.abstractData mining tools are widely used in computer networks. The well-known and mostly used tools to secure computers and network systems are WEKA and TANAGRA. The purpose of this study is to compare these two tools in terms of detection accuracy and computation time. This comparison was conducted using a well-known NSL-KDD dataset. Experiments show that TANAGRA achieves better results than WEKA in detection accuracy. But, TANAGRA is competitive with WEKA in terms of computation time.
dc.identifier.isbn978-1-6654-7825-0
dc.identifier.issn10.1109/ICISAT54145.2021.9678485
dc.identifier.urihttps://dl.cerist.dz/handle/CERIST/1023
dc.publisherIEEEfr
dc.relation.ispartofseriesInternational Conference on Information Systems and Advanced Technologies (ICISAT); 27-28 December 2021
dc.relation.pages3 p.
dc.relation.placeTebessa, Algeria
dc.structureTechnologie Internet et Réseaux
dc.subjectTANAGRA
dc.subjectWeka
dc.subjectNSL KDD dataset
dc.subjectData mining
dc.subjectIDS
dc.subjectExperimental comparison
dc.titleIntrusion Detection Systems using Data Mining Techniques: A comparative study
dc.typeConference paper
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