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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 11–20 of 261 papers

TitleStatusHype
Efficient Deep CNN-BiLSTM Model for Network Intrusion DetectionCode1
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoTCode1
FedMSE: Federated learning for IoT network intrusion detectionCode1
FlowTransformer: A Transformer Framework for Flow-based Network Intrusion Detection SystemsCode1
Adaptive Intrusion Detection in the Networking of Large-Scale LANs with Segmented Federated LearningCode1
An Intrusion Detection System based on Deep Belief NetworksCode1
AnomalyDAE: Dual autoencoder for anomaly detection on attributed networksCode1
A flow-based IDS using Machine Learning in eBPFCode1
A Study on Transferability of Deep Learning Models for Network Intrusion DetectionCode1
IoTGeM: Generalizable Models for Behaviour-Based IoT Attack DetectionCode1
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