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- W4313531834 endingPage "109553" @default.
- W4313531834 startingPage "109553" @default.
- W4313531834 abstract "Distributed Denial of Service (DDoS) attack is one of the biggest cyber threats. DDoS attacks have evolved in quantity and volume to evade detection and increase damage. Changes during the COVID-19 pandemic have left traditional perimeter-based security measures vulnerable to attackers that have diversified their activities by targeting health services, e-commerce, and educational services. DDoS attack prediction searches for signals of attack preparation to warn about the imminence of the attack. Prediction is necessary to handle high-volumetric DDoS attacks and to increase the time to defend against them. This survey article presents the classification of studies from the literature comprising the current state-of-the-art on DDoS attack prediction. It highlights the results of this extensive literature review categorizing the works by prediction time, architecture, employed methodology, and the type of data utilized to predict attacks. Further, this survey details each identified study and, finally, it emphasizes the research opportunities to evolve the DDoS attack prediction state-of-the-art." @default.
- W4313531834 created "2023-01-06" @default.
- W4313531834 creator A5003131477 @default.
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- W4313531834 creator A5028233772 @default.
- W4313531834 date "2023-02-01" @default.
- W4313531834 modified "2023-10-16" @default.
- W4313531834 title "Distributed denial of service attack prediction: Challenges, open issues and opportunities" @default.
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- W4313531834 doi "https://doi.org/10.1016/j.comnet.2022.109553" @default.
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