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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 221–230 of 261 papers

TitleStatusHype
Intrusion Detection using Sequential Hybrid Model—0
ASNM Datasets: A Collection of Network Traffic Features for Testing of Adversarial Classifiers and Network Intrusion Detectors—0
WOTBoost: Weighted Oversampling Technique in Boosting for imbalanced learning—0
LuNet: A Deep Neural Network for Network Intrusion DetectionCode0
A Transfer Learning Approach for Network Intrusion Detection—0
SynGAN: Towards Generating Synthetic Network Attacks using GANs—0
Sparse Bayesian approach for metric learning in latent spaceCode0
Analyzing and Storing Network Intrusion Detection Data using Bayesian Coresets: A Preliminary Study in Offline and Streaming Settings—0
A Combination of Temporal Sequence Learning and Data Description for Anomaly-based NIDS—0
Mimic Learning to Generate a Shareable Network Intrusion Detection Model—0
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