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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 71–80 of 261 papers

TitleStatusHype
A Novel Resampling Technique for Imbalanced Dataset Optimization—0
A Hypergraph-Based Machine Learning Ensemble Network Intrusion Detection System—0
A Grassmannian Approach to Zero-Shot Learning for Network Intrusion Detection—0
A Novel Deep Learning based Model to Defend Network Intrusion Detection System against Adversarial Attacks—0
A Defensive Framework Against Adversarial Attacks on Machine Learning-Based Network Intrusion Detection Systems—0
Detecting Clusters of Anomalies on Low-Dimensional Feature Subsets with Application to Network Traffic Flow Data—0
Detect & Reject for Transferability of Black-box Adversarial Attacks Against Network Intrusion Detection Systems—0
Deep Neural Networks based Meta-Learning for Network Intrusion Detection—0
Deep PackGen: A Deep Reinforcement Learning Framework for Adversarial Network Packet Generation—0
1D CNN Based Network Intrusion Detection with Normalization on Imbalanced Data—0
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