Analysis of NSL-KDD Dataset for Fuzzy Based Intrusion Detection System

dc.contributor.authorMukosera, Macdonald
dc.contributor.authorMpofu, Thabiso Peter
dc.contributor.authorMasaiti, Budwell
dc.date.accessioned2023-06-19T12:53:14Z
dc.date.available2023-06-19T12:53:14Z
dc.date.issued2012-01-08
dc.descriptionAnalysis of NSL-KDD Dataset for Fuzzy Based Intrusion Detection Systemen_US
dc.description.abstractIn a bid to provide useful information for intrusion detection, we focused on analyzing the NSL-KDD dataset. In this analysis, we seek to simplify the process of mining fuzzy rules by reducing the features and categorizing the dataset into various smaller clusters as smaller units of the dataset are easier to work with than the whole single large dataset. It is less complex to observe and discover sound fuzzy rules from a smaller dataset and this work serves as a foundation to a fuzzy logic based intrusion detection system. This paper presents a methodology for data preprocessing towards an intrusion detection system and Microsoft excel was used in the process.en_US
dc.identifier.citationMukosera, M., Mpofu, T.P., & Masaiti, B. (2014). Analysis of NSL-KDD Dataset for Fuzzy Based Intrusion Detection System.en_US
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/768
dc.language.isoenen_US
dc.publisherInternational Journal of Science and Research (IJSR)en_US
dc.relation.ispartofseriesInternational Journal of Science and Research (IJSR);
dc.subjectInternational Journal of Science and Research (IJSR)en_US
dc.titleAnalysis of NSL-KDD Dataset for Fuzzy Based Intrusion Detection Systemen_US
dc.typeArticleen_US

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