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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 201–210 of 261 papers

TitleStatusHype
Adversarial Examples in Constrained Domains—0
DualNet: Locate Then Detect Effective Payload with Deep Attention Network—0
Spiking Neural Networks with Single-Spike Temporal-Coded Neurons for Network Intrusion Detection—0
The Effective Methods for Intrusion Detection With Limited Network Attack Data: Multi-Task Learning and Oversampling—0
Machine Learning Applications in Misuse and Anomaly Detection—0
Self-Organizing Map assisted Deep Autoencoding Gaussian Mixture Model for Intrusion DetectionCode0
Network Intrusion Detection Using Wrapper-based Decision Tree for Feature Selection—0
Multi-Stage Optimized Machine Learning Framework for Network Intrusion Detection—0
EagerNet: Early Predictions of Neural Networks for Computationally Efficient Intrusion DetectionCode0
Adversarial Machine Learning in Network Intrusion Detection Systems—0
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