Results 101 to 110 of about 29,505 (203)

Fuzzy Observation of DDoS Attack

open access: yes, 2017
DDoS attacks are able to block Web servers. Such attacks could be started from anywhere in the network. This chapter presents the possibility of using Ordered Fuzzy Numbers (OFNs) for observation of a DDoS attack. The proposed algorithm could be implemented on routers and predict the moment of the attack.
openaire   +1 more source

Classification of DDoS attack traffic on SDN network environment using deep learning

open access: yesCybersecurity
Distributed Denial of Service (DDoS) attack is a major threat to the Internet of Things (IoT), Software Defined Networks (SDN), and Cloud Computing Networks.
Urikhimbam Boby Clinton   +2 more
doaj   +1 more source

A Data Enhancement Algorithm for DDoS Attacks Using IoT. [PDF]

open access: yesSensors (Basel), 2023
Lv H, Du Y, Zhou X, Ni W, Ma X.
europepmc   +1 more source

Multi-Stage Adversarial Defense for Online DDoS Attack Detection System in IoT

open access: yesIEEE Access
Machine learning-based Distributed Denial of Service (DDoS) attack detection systems have proven effective in detecting and preventing DDoD attacks in Internet of Things (IoT) systems.
Yonas Kibret Beshah   +2 more
doaj   +1 more source

Prediction of DDoS attacks in agriculture 4.0 with the help of prairie dog optimization algorithm with IDSNet. [PDF]

open access: yesSci Rep, 2023
Vatambeti R   +5 more
europepmc   +1 more source

Research on low-rate DDoS attack of SDN network in cloud environment

open access: yesTongxin xuebao, 2019
Aiming at the problems of low-rate DDoS attack detection accuracy in cloud SDN network and the lack of unified framework for data plane and control plane low-rate DDoS attack detection and defense,a unified framework for low-rate DDoS attack detection ...
Xingshu CHEN   +4 more
doaj   +2 more sources

DDoS family: A novel perspective for massive types of DDoS attacks

open access: yesComputers & Security
Distributed Denial of Service (DDoS) defense is a profound research problem. In recent years, adversaries tend to complicate their attack strategies by crafting vast DDoS variants. On the one hand, this trend exacerbates both extremes of classification granularity (i.e., binary and attack level) in existing machine learning methods.
Ziming Zhao 0008   +7 more
openaire   +2 more sources

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