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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 91–100 of 261 papers

TitleStatusHype
DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection—0
Domain Knowledge Aided Explainable Artificial Intelligence for Intrusion Detection and Response—0
DRL-GAN: A Hybrid Approach for Binary and Multiclass Network Intrusion Detection—0
DualNet: Locate Then Detect Effective Payload with Deep Attention Network—0
ASNM Datasets: A Collection of Network Traffic Features for Testing of Adversarial Classifiers and Network Intrusion Detectors—0
Early Detection of Network Attacks Using Deep Learning—0
Deep Adversarial Learning in Intrusion Detection: A Data Augmentation Enhanced Framework—0
EdgeServe: A Streaming System for Decentralized Model Serving—0
A Novel Approach To Network Intrusion Detection System Using Deep Learning For Sdn: Futuristic Approach—0
Efficient Network Representation for GNN-based Intrusion Detection—0
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