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- W4386014784 abstract "DDoS assaults are a danger to network security because they overwhelm target networks with malicious traffic, making them unusable as a result. One of the most significant concerns is the lack of a real-time DDoS attack detector that requires low processing power. When it comes to testing novel detection algorithms and approaches, good datasets are vital. After evaluating current datasets, the authors of this paper propose a new DDoS taxonomy. After that, we produce a new dataset, CICDoS2019 that addresses all of our issues. Third, we offer a new family detection and classification technique based on network flow features extracted from the created dataset, which we call FlowNet. Finally, we rank the most relevant feature sets for identifying distributed denial-of-service (DDoS) assaults." @default.
- W4386014784 created "2023-08-21" @default.
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- W4386014784 date "2023-01-01" @default.
- W4386014784 modified "2023-09-27" @default.
- W4386014784 title "A Review of DDoS Evaluation Dataset: CICDDoS2019 Dataset" @default.
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- W4386014784 doi "https://doi.org/10.1007/978-981-99-3691-5_34" @default.
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