A flexible SDN-based architecture for identifying and mitigating low-rate DDoS attacks using machine learning

JA Perez-Diaz, IA Valdovinos, KKR Choo, D Zhu - IEEE Access, 2020 - ieeexplore.ieee.org
While there have been extensive studies of denial of service (DoS) attacks and DDoS attack
mitigation, such attacks remain challenging to mitigate. For example, Low-Rate DDoS (LR …

[HTML][HTML] A dynamic MLP-based DDoS attack detection method using feature selection and feedback

M Wang, Y Lu, J Qin - Computers & Security, 2020 - Elsevier
Abstract Distributed Denial of Service (DDoS) attack is a stubborn network security problem.
Various machine learning-based methods have been proposed to detect such attacks …

Voting extreme learning machine based distributed denial of service attack detection in cloud computing

GS Kushwah, V Ranga - Journal of Information Security and Applications, 2020 - Elsevier
Distributed denial of service attack is one of the most dangerous attacks in cloud computing.
This attack makes the cloud services inaccessible to the end-users by exhausting resources …

On sustained zero trust conceptualization security for mobile core networks in 5g and beyond

Y Bello, AR Hussein, M Ulema… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The rapid increase in data traffic is forcing mobile network operators to enhance and expand
their network infrastructure to meet the new requirements of customers' Service Level …

[PDF][PDF] DDoS attack intrusion detection system based on hybridization of CNN and LSTM

ASA Issa, Z Albayrak - Acta Polytechnica Hungarica, 2023 - researchgate.net
A distributed denial-of-service (DDoS) attack is one of the most pernicious threats to network
security. DDoS attacks are considered one of the most common attacks among all network …

Detecting DDoS attacks in cloud computing using extreme learning machine and adaptive differential evolution

GS Kushwah, V Ranga - Wireless Personal Communications, 2022 - Springer
Distributed denial of service (DDoS) attacks disrupt the availability of cloud services. The
detection of these attacks is a major challenge in the cloud computing environment. Machine …

[PDF][PDF] Ddos detection in Software-Defined Network (Sdn) using machine learning

H Alubaidan, R Alzaher, M AlQhatani… - Int J Cybernetics …, 2023 - ijcionline.com
In recent years, the concept of cloud computing and the software-defined network (SDN)
have spread widely. The services provided by many sectors such as medicine, education …

Multi-modal noise-robust DDoS attack detection architecture in large-scale networks based on tensor SVD

J Xu, X Li, P Wang, X Jin, S Yao - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Distributed Denial of Service (DDoS) attacks consumes the resources of traditional or cloud
computing networks, resulting in the network unable to provide normal services. Therefore …

Tensor based framework for Distributed Denial of Service attack detection

JPA Maranhão, JPCL da Costa, E Javidi… - Journal of Network and …, 2021 - Elsevier
Abstract Distributed Denial of Service (DDoS) attacks are one of the most important security
threats, since multiple compromised systems perform massive attacks over a victim …

Enhancing Cloud Computing Analysis: A CCE-Based HTTP-GET Log Dataset

ZR Alashhab, M Anbar, SDA Rihan, BA Alabsi… - Applied Sciences, 2023 - mdpi.com
The Hypertext Transfer Protocol (HTTP) is a common target of distributed denial-of-service
(DDoS) attacks in today's cloud computing environment (CCE). However, most existing …