Nov 20, 2023 · This paper proposes an APT attack detection method based on Graph Convolutional Neural Networks (GCN) to address the ever-evolving network ...
In this article, we propose an IG model for detecting APT attacks based on network traffic. The model consists of two main layers: the I layer -Inference ...
Missing: Neural | Show results with:Neural
Hyperparameter settings in APT detection method based on graph convolutional neural network ... APT Attack Detection Based on Graph Convolutional Neural Networks.
Here, the author proposed an approach based on the Spatio-Temporal Graph Convolutional Networks model for detecting DDoS attacks in a network environment. [11] ...
Jan 1, 2023 · In this paper, a new APT attack model, which is the combination of three different neural network layers including: Multi-layer Perceptron (MLP) ...
APT attack detection based on graph convolutional neural networks. Int J Comput Intell Syst. (2023). Y. N. Deepro: provenance-based APT campaigns detection via ...
Abstract— In this article, we propose an IG model for detecting APT attacks based on network traffic. The model consists of two main layers: the I layer ...
Missing: Neural | Show results with:Neural
Feb 3, 2024 · This paper proposes a GNN-AP structure to first identify APT attacks by removing ambiguous alert such as non-malicious attack alert and false ...
Jun 24, 2024 · The FIE combined model has the function of aggregating and extracting unusual behaviors of APT IPs in network traffic. The RL method proposed in ...
Using Inference and Graph Convolutional Networks for APT Attack Detection ... APT attack detection based on flow network analysis techniques using deep learning.
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