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Detecting and locating configuration errors in IP VPNs with ...
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由 EH Mohammedi 著作2022被引用 2 次 — In this paper, we propose a Graph Neural Network (GNN) based approach to detect and locate configuration errors in IP Virtual Private Networks (VPNs).
Detecting and locating configuration errors in IP VPNs with ...
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In this paper, we propose a Graph Neural Network (GNN) based approach to detect and locate configuration errors in IP Virtual Private Networks (VPNs). Two GNN ...
Detecting and locating configuration errors in IP VPNs with ...
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由 EH Mohammedi 著作2022被引用 2 次 — Results show a high level of accuracy in detecting configuration errors, more than 80 or 90 percent depending on the type of error. The remainder of this paper ...
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Detecting and locating configuration errors in IP VPNs with ...
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In this paper, we propose a Graph Neural Network (GNN) based approach to detect and locate configuration errors in IP Virtual Private Networks (VPNs). Two GNN ...
El-Heithem MOHAMMEDI
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Configuration faults detection in IP Virtual Private Networks based on machine learning · Detecting and locating configuration errors in IP VPNs with Graph ...
Configuration faults detection in IP Virtual Private Networks ...
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由 EH Mohammedi 著作2020被引用 3 次 — In this paper, we propose another approach based on machine learning to detect and locate connectivity incidents related to configuration faults ...
jwwthu/GNN-Communication-Networks
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Detecting and locating configuration errors in IP VPNs with Graph Neural Networks[C]//NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium.
Identifying VPN Servers through Graph-Represented Behaviors
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由 C Wang 著作2024被引用 1 次 — In this work, we propose VPNChecker, which utilizes the graph-represented behaviors to detect VPN servers in real-world scenarios.
Introduction to Graph Neural Networks | Request PDF
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A GNN model is composed of several computational modules distributed over a set of layers. ... Detecting and locating configuration errors in IP VPNs ...
Network Flow Graph Neural Networks for Malware ...
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由 J Busch 著作2021被引用 64 次 — Our approach first extracts flow graphs and subsequently classifies them using a novel edge feature-based graph neural network model. We present ...