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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 101–110 of 261 papers

TitleStatusHype
EG-ConMix: An Intrusion Detection Method based on Graph Contrastive Learning—0
DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection—0
Energy-based Models for Video Anomaly Detection—0
A Robust Comparison of the KDDCup99 and NSL-KDD IoT Network Intrusion Detection Datasets Through Various Machine Learning Algorithms—0
Analyzing and Storing Network Intrusion Detection Data using Bayesian Coresets: A Preliminary Study in Offline and Streaming Settings—0
DI-NIDS: Domain Invariant Network Intrusion Detection System—0
Ensemble Classifier Design Tuned to Dataset Characteristics for Network Intrusion Detection—0
EPASAD: Ellipsoid decision boundary based Process-Aware Stealthy Attack Detector—0
Evaluating Generative Models for Tabular Data: Novel Metrics and Benchmarking—0
Are We There Yet? Unraveling the State-of-the-Art Graph Network Intrusion Detection Systems—0
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