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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 161–170 of 261 papers

TitleStatusHype
Training a Bidirectional GAN-based One-Class Classifier for Network Intrusion Detection—0
Transforming In-Vehicle Network Intrusion Detection: VAE-based Knowledge Distillation Meets Explainable AI—0
Two-stage Deep Stacked Autoencoder with Shallow Learning for Network Intrusion Detection System—0
Untargeted White-box Adversarial Attack with Heuristic Defence Methods in Real-time Deep Learning based Network Intrusion Detection System—0
Use Dimensionality Reduction and SVM Methods to Increase the Penetration Rate of Computer Networks—0
V-CNN: When Convolutional Neural Network encounters Data Visualization—0
WeiDetect: Weibull Distribution-Based Defense against Poisoning Attacks in Federated Learning for Network Intrusion Detection Systems—0
WOTBoost: Weighted Oversampling Technique in Boosting for imbalanced learning—0
Hybrid Model For Intrusion Detection Systems—0
IGRF-RFE: A Hybrid Feature Selection Method for MLP-based Network Intrusion Detection on UNSW-NB15 Dataset—0
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