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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 141–150 of 261 papers

TitleStatusHype
LBDMIDS: LSTM Based Deep Learning Model for Intrusion Detection Systems for IoT Networks—0
On Generalisability of Machine Learning-based Network Intrusion Detection Systems—0
Ensemble Classifier Design Tuned to Dataset Characteristics for Network Intrusion Detection—0
Representation Learning for Content-Sensitive Anomaly Detection in Industrial NetworksCode1
Dependable Intrusion Detection System for IoT: A Deep Transfer Learning-based Approach—0
EPASAD: Ellipsoid decision boundary based Process-Aware Stealthy Attack Detector—0
IGRF-RFE: A Hybrid Feature Selection Method for MLP-based Network Intrusion Detection on UNSW-NB15 Dataset—0
The Cross-evaluation of Machine Learning-based Network Intrusion Detection SystemsCode0
Prepare for Trouble and Make it Double. Supervised and Unsupervised Stacking for AnomalyBased Intrusion Detection—0
NetSentry: A Deep Learning Approach to Detecting Incipient Large-scale Network Attacks—0
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