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

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dc.creatorElisa, Noe
dc.creatorYang, Longzhi
dc.creatorFu, Xin
dc.creatorNaik, Nitin
dc.date2020-11-26T09:34:16Z
dc.date2020-11-26T09:34:16Z
dc.date2019
dc.date.accessioned2022-10-20T13:45:32Z
dc.date.available2022-10-20T13:45:32Z
dc.descriptionAbstract. Full Text Conference Article available at https://ieeexplore.ieee.org/abstract/document/8859006/keywords#keywords
dc.descriptionDendritic 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.
dc.identifierElisa, 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). IEEE
dc.identifierDOI: 10.1109/FUZZ-IEEE.2019.8859006
dc.identifierhttp://hdl.handle.net/20.500.12661/2635
dc.identifier.urihttp://hdl.handle.net/20.500.12661/2635
dc.languageen
dc.publisherIEEE
dc.subjectDendritic cell algorithm
dc.subjectDendritic cell
dc.subjectComputer networks
dc.subjectFuzzy inference
dc.subjectFuzzy inference system
dc.subjectNetwork intrusion
dc.subjectNetwork intrusion detection
dc.subjectClassification algorithm
dc.subjectImmune-inspired classification algorithm
dc.titleDendritic cell algorithm enhancement using fuzzy inference system for network intrusion detection
dc.title2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
dc.typeConference Proceedings

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