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dc.contributor.author Amalraj, CRJ
dc.contributor.author Madhusankha, PGG
dc.contributor.editor Piyatilake, ITS
dc.contributor.editor Thalagala, PD
dc.contributor.editor Ganegoda, GU
dc.contributor.editor Thanuja, ALARR
dc.contributor.editor Dharmarathna, P
dc.date.accessioned 2024-02-06T06:27:51Z
dc.date.available 2024-02-06T06:27:51Z
dc.date.issued 2023-12-07
dc.identifier.uri http://dl.lib.uom.lk/handle/123/22185
dc.description.abstract This research focuses on identifying DDoS attacks using an ensemble learning approach that incorporates blending techniques. We developed an innovative methodology by selecting the 21 most significant features from the CIC-DDoS2019 dataset. To improve classification accuracy, we used a two-layer blending ensemble technique. In the first layer, we combined Decision Tree, Logistic Regression, and KNN classifiers, while the second layer used a Random Forest classifier. The model achieved exceptional results, with a 99.94% accuracy score and a 97.35% F1 score for detecting DDoS attacks accurately. We also created a user-friendly web portal to make the model accessible for individuals in network security, regardless of their technical expertise. This approach advances DDoS attack detection and enhances usability for users in the field of network security. en_US
dc.language.iso en en_US
dc.publisher Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa. en_US
dc.subject DDoS attacks en_US
dc.subject CIC-DDoS2019 en_US
dc.subject Blending ensemble en_US
dc.title Enhancing ddos attack detection via blending ensemble learning en_US
dc.type Conference-Full-text en_US
dc.identifier.faculty IT en_US
dc.identifier.department Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa. en_US
dc.identifier.year 2023 en_US
dc.identifier.conference 8th International Conference in Information Technology Research 2023 en_US
dc.identifier.place Moratuwa, Sri Lanka en_US
dc.identifier.pgnos pp. 1-6 en_US
dc.identifier.proceeding Proceedings of the 8th International Conference in Information Technology Research 2023 en_US
dc.identifier.email amalraj@uom.lk en_US
dc.identifier.email madhusankhamrtit97@gmail.com en_US


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  • ICITR - 2023 [47]
    International Conference on Information Technology Research (ICITR)

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