SSK-DDoS: distributed stream processing framework based classification system for DDoS attacks. [PDF]
Cluster Comput, 2022 Patil NV, Krishna CR, Kumar K.
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, 2023 Distributed Denial-of-Service (DDoS) is one of the most common cyberattack used by malicious actors. It has been evolving over the years, using more complex techniques to increase its attack power and surpass the current defense mechanisms. Due to the existent number of different DDoS attacks and their constant evolution, companies need to be ...
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Transport and Application Layer DDoS Attacks Detection to IoT Devices by Using Machine Learning and Deep Learning Models. [PDF]
Sensors (Basel), 2022 Almaraz-Rivera JG +2 more
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A hybrid machine learning approach for detecting DDoS attacks in software-defined networks. [PDF]
Sci RepMahar IA +5 more
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A statistical approach to secure health care services from DDoS attacks during COVID-19 pandemic. [PDF]
Neural Comput Appl, 2021 Zhou Z +4 more
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A hybrid deep learning model for detection and mitigation of DDoS attacks in VANETs. [PDF]
Sci RepJayakrishna N, Prasanth NN.
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Nature-inspired swarm optimization paradigms for securing semantic web frameworks against DDoS attacks: a computational approach. [PDF]
Sci RepGanguli C +3 more
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A lightweight blockchain based scalable and collaborative mitigation framework against new flow DDoS attacks in SDN enabled autonomous systems. [PDF]
Sci RepGarg S, Goyal S, Bhandari A.
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A Multi-Class Intrusion Detection System for DDoS Attacks in IoT Networks Using Deep Learning and Transformers. [PDF]
Sensors (Basel)Wahab SA +5 more
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Securing IoT Networks Against DDoS Attacks: A Hybrid Deep Learning Approach. [PDF]
Sensors (Basel)Ain NU +4 more
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