A hybrid machine learning approach for detecting DDoS attacks in software-defined networks. [PDF]
Mahar IA +5 more
europepmc +1 more source
Optimized CatBoost machine learning (OCML) for DDoS detection in cloud virtual machines with time-series and adversarial robustness. [PDF]
Samy H, Bahaa-Eldin AM, Sobh MA, Taha A.
europepmc +1 more source
Dynamic graph neural network-based framework to increase detection accuracy in SDN under DDOS. [PDF]
Kalafy SAA, Pashazadeh S, Salehpour P.
europepmc +1 more source
Mitigating distributed denial of service attacks using attribute subset selection with temporal convolutional networks. [PDF]
Alamro H +7 more
europepmc +1 more source
Lightweight and Energy-Aware Intrusion Detection for Industrial IoT Using TinyML and Edge AI. [PDF]
Nassef L +7 more
europepmc +1 more source
Datasets for distributed denial-of-service detection in healthcare internet of things environments. [PDF]
Akhi M, Eising C, Dhirani LL.
europepmc +1 more source
DMSTG-AD: an SDN intrusion detection method based on dynamic multi-scale spatio-temporal graph neural network. [PDF]
Zhao J, Zhang D, He Q, Lin M, Yang Y.
europepmc +1 more source
Correction: NIDD-enabled lightweight intrusion detection for effective DDoS mitigation in 5G and beyond. [PDF]
Javid I +6 more
europepmc +1 more source
Modelling of hybrid deep learning framework with recursive feature elimination for distributed denial of service attack detection systems. [PDF]
Alkhliwi S.
europepmc +1 more source
A dataset collected in real-world industrial control systems for network attack detection. [PDF]
Zhou X +9 more
europepmc +1 more source

