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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 31–40 of 261 papers

TitleStatusHype
An Intrusion Detection System based on Deep Belief NetworksCode1
Anomal-E: A Self-Supervised Network Intrusion Detection System based on Graph Neural NetworksCode1
Applying Self-supervised Learning to Network Intrusion Detection for Network Flows with Graph Neural NetworkCode1
AnomalyDAE: Dual autoencoder for anomaly detection on attributed networksCode1
Hybrid Isolation Forest - Application to Intrusion DetectionCode0
Implementing Lightweight Intrusion Detection System on Resource Constrained DevicesCode0
Evaluating the Potential of Quantum Machine Learning in Cybersecurity: A Case-Study on PCA-based Intrusion Detection SystemsCode0
Evaluating Shallow and Deep Neural Networks for Network Intrusion Detection Systems in Cyber SecurityCode0
Enhanced Convolution Neural Network with Optimized Pooling and Hyperparameter Tuning for Network Intrusion DetectionCode0
EagerNet: Early Predictions of Neural Networks for Computationally Efficient Intrusion DetectionCode0
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