This paper proposes GoGDDoS, a multi-classifier for DDoS attacks. Concretely, we construct GoG traffic graph to clearly compress relationships between packets ...
GoGDDoS: A Multi-classifier for DDoS Attacks. Using Graph Neural Networks ... GoGDDoS constructs GoG (Graph of Graph) traffic graph by merging the ...
Effective DDoS Attack Detection Using Graph Neural Networks
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GraphDDoS, a GNN-based approach for detecting DDoS attacks using endpoint traffic graphs that outperforms the state-of-the-art DL-based approaches in terms ...
Nov 11, 2021 · This is done to identify and classify the various types of DDoS attacks. The result was compared with previous works treating the same dataset ...
Nov 17, 2023 · Network Flow Analytics: Multi-Class Classification of DDoS Attacks ... GoGDDoS: A Multi-Classifier for DDoS Attacks Using Graph Neural Networks.
GoGDDoS: A Multi-Classifier for DDoS Attacks Using Graph Neural Networks ... Graph Neural Network model to mine potential attack patterns from GoG traffic graph.
Temporal-Gated Graph Neural Network with Graph Sampling for Multi-step Attack ... GoGDDoS: A Multi-Classifier for DDoS Attacks Using Graph Neural Networks[C] ...
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Nov 11, 2021 · The objective of this work is based on the exploration and choice of a set of data that represents DDoS attack events, on their treatment in a ...
Missing: GoGDDoS: Graph
May 18, 2024 · To detect such attacks, graph neural network based methods have shown promising results by modeling the system's events as a graph. However, ...
Missing: GoGDDoS: | Show results with:GoGDDoS:
May 30, 2022 · Our proposed hybrid model incorporates Convolution Neural Network (CNN), Long Short Term Memory (LSTM), and Gated Recurrent Unit (GRU), and we ...
Missing: GoGDDoS: | Show results with:GoGDDoS: