Results 131 to 140 of about 26,597 (201)

Multi-Channel Power Scheduling Based on Intrusion Detection System Under DDoS Attack: A Starkberg Game Approach. [PDF]

Sensors (Basel)
Yi Y, Peng L.
europepmc   +1 more source

Effective DDoS attack detection in software-defined vehicular networks using statistical flow analysis and machine learning. [PDF]

PLoS One
Babbar H, Rani S, Driss M.
europepmc   +1 more source

IoT-DH dataset for classification, identification, and detection DDoS attack in IoT. [PDF]

Data Brief
Saif S, Widyawan W, Ferdiana R.
europepmc   +1 more source

DDoS attack detection in smart grid network using reconstructive machine learning models. [PDF]

PeerJ Comput Sci
Naqvi SSA, Li Y, Uzair M.
europepmc   +1 more source

A novel multi-scale CNN and Bi-LSTM arbitration dense network model for low-rate DDoS attack detection. [PDF]

Sci Rep
Yin X, Fang W, Liu Z, Liu D.
europepmc   +1 more source

Strengthening network DDOS attack detection in heterogeneous IoT environment with federated XAI learning approach.

Sci Rep
Almadhor A, Altalbe A, Bouazzi I, Hejaili AA, Kryvinska N.   +4 more
europepmc   +1 more source

Deep learning-based HTTP TRACE flood detection in wireless sensor network using deep spectral multi-layer convolutional neural network. [PDF]

Sci Rep
Tamilselvi S, Shieh CS, Horng MF, Shanker NR.   +3 more
europepmc   +1 more source

A hybrid machine learning approach for detecting DDoS attacks in software-defined networks. [PDF]

Sci Rep
Mahar IA, Aziz K, Chakrabarti P, Ahmed N, Ladan M, Javed Y.   +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]

Sci Rep
Samy H, Bahaa-Eldin AM, Sobh MA, Taha A.
europepmc   +1 more source

A dataset collected in real-world industrial control systems for network attack detection. [PDF]

Sci Data
Zhou X, Cheng Z, Wang C, Wang S, Tao C, Zhou Z, Chen X, Luo J, Wang D, Zhou H.   +9 more
europepmc   +1 more source