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Network Intrusion Detection

Network intrusion detection is the task of monitoring network traffic to and from all devices on a network in order to detect computer attacks.

Papers

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Showing 1–10 of 261 papers

TitleStatusHype
CAGN-GAT Fusion: A Hybrid Contrastive Attentive Graph Neural Network for Network Intrusion DetectionCode1
Continual Learning with Strategic Selection and Forgetting for Network Intrusion DetectionCode1
FedMSE: Federated learning for IoT network intrusion detectionCode1
XG-NID: Dual-Modality Network Intrusion Detection using a Heterogeneous Graph Neural Network and Large Language ModelCode1
PolyLUT-Add: FPGA-based LUT Inference with Wide InputsCode1
Problem space structural adversarial attacks for Network Intrusion Detection Systems based on Graph Neural NetworksCode1
Applying Self-supervised Learning to Network Intrusion Detection for Network Flows with Graph Neural NetworkCode1
On the Cross-Dataset Generalization of Machine Learning for Network Intrusion DetectionCode1
Improving Transferability of Network Intrusion Detection in a Federated Learning SetupCode1
A Study on Transferability of Deep Learning Models for Network Intrusion DetectionCode1
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