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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 21–30 of 261 papers

TitleStatusHype
Applying Self-supervised Learning to Network Intrusion Detection for Network Flows with Graph Neural NetworkCode1
Improving Transferability of Network Intrusion Detection in a Federated Learning SetupCode1
CAGN-GAT Fusion: A Hybrid Contrastive Attentive Graph Neural Network for Network Intrusion DetectionCode1
Bridging the gap to real-world for network intrusion detection systems with data-centric approachCode1
Continual Learning with Strategic Selection and Forgetting for Network Intrusion DetectionCode1
LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput ApplicationsCode1
Efficient Deep CNN-BiLSTM Model for Network Intrusion DetectionCode1
On the Cross-Dataset Generalization of Machine Learning for Network Intrusion DetectionCode1
Edge-Detect: Edge-centric Network Intrusion Detection using Deep Neural NetworkCode1
Representation Learning for Content-Sensitive Anomaly Detection in Industrial NetworksCode1
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