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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
Efficient Deep CNN-BiLSTM Model for Network Intrusion DetectionCode1
Evaluating and Improving Adversarial Robustness of Machine Learning-Based Network Intrusion DetectorsCode1
LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput ApplicationsCode1
AnomalyDAE: Dual autoencoder for anomaly detection on attributed networksCode1
Poster: Enhancing GNN Robustness for Network Intrusion Detection via Agent-based Analysis—0
KnowML: Improving Generalization of ML-NIDS with Attack Knowledge Graphs—0
Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning—0
A Robust PPO-optimized Tabular Transformer Framework for Intrusion Detection in Industrial IoT SystemsCode0
CSAGC-IDS: A Dual-Module Deep Learning Network Intrusion Detection Model for Complex and Imbalanced Data—0
Constrained Network Adversarial Attacks: Validity, Robustness, and Transferability—0
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