Dendritic cell algorithm enhancement using fuzzy inference system for network intrusion detection

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dc.contributor.authorElisa, Noe
dc.contributor.authorYang, Longzhi
dc.contributor.authorFu, Xin
dc.contributor.authorNaik, Nitin
dc.date.accessioned2020-11-26T09:34:16Z
dc.date.available2020-11-26T09:34:16Z
dc.date.issued2019
dc.descriptionAbstract. Full Text Conference Article available at https://ieeexplore.ieee.org/abstract/document/8859006/keywords#keywordsen_US
dc.description.abstractDendritic cell algorithm (DCA) is an immune-inspired classification algorithm which is developed for the purpose of anomaly detection in computer networks. The DCA uses a weighted function in its context detection phase to process three categories of input signals including safe, danger and pathogenic associated molecular pattern to three output context values termed as co-stimulatory, mature and semi-mature, which are then used to perform classification. The weighted function used by the DCA requires either manually pre-defined weights usually provided by the immunologists, or empirically derived weights from the training dataset. Neither of these is sufficiently flexible to work with different datasets to produce optimum classification result. To address such limitation, this work proposes an approach for computing the three output context values of the DCA by employing the recently proposed TSK+ fuzzy inference system, such that the weights are always optimal for the provided data set regarding a specific application. The proposed approach was validated and evaluated by applying it to the two popular datasets KDD99 and UNSW NB15. The results from the experiments demonstrate that, the proposed approach outperforms the conventional DCA in terms of classification accuracy.en_US
dc.identifier.citationElisa, N., Yang, L., Fu, X., & Naik, N. (2019, June). Dendritic cell algorithm enhancement using fuzzy inference system for network intrusion detection. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1-6). IEEEen_US
dc.identifier.otherDOI: 10.1109/FUZZ-IEEE.2019.8859006
dc.identifier.urihttp://hdl.handle.net/20.500.12661/2635
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectDendritic cell algorithmen_US
dc.subjectDendritic cellen_US
dc.subjectComputer networksen_US
dc.subjectFuzzy inferenceen_US
dc.subjectFuzzy inference systemen_US
dc.subjectNetwork intrusionen_US
dc.subjectNetwork intrusion detectionen_US
dc.subjectClassification algorithmen_US
dc.subjectImmune-inspired classification algorithmen_US
dc.titleDendritic cell algorithm enhancement using fuzzy inference system for network intrusion detectionen_US
dc.title.alternative2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)en_US
dc.typeConference Proceedingsen_US
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