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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
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly DetectionCode1
Representation Learning for Content-Sensitive Anomaly Detection in Industrial NetworksCode1
Bridging the gap to real-world for network intrusion detection systems with data-centric approachCode1
Unveiling the potential of Graph Neural Networks for robust Intrusion DetectionCode1
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoTCode1
A flow-based IDS using Machine Learning in eBPFCode1
Edge-Detect: Edge-centric Network Intrusion Detection using Deep Neural NetworkCode1
Adaptive Intrusion Detection in the Networking of Large-Scale LANs with Segmented Federated LearningCode1
Intrusion Detection with Segmented Federated Learning for Large-Scale Multiple LANsCode1
Enhancing Robustness Against Adversarial Examples in Network Intrusion Detection SystemsCode1
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