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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 201–225 of 261 papers

TitleStatusHype
Self-Organizing Map assisted Deep Autoencoding Gaussian Mixture Model for Intrusion DetectionCode0
Network Intrusion Detection Using Wrapper-based Decision Tree for Feature Selection—0
Enhancing Robustness Against Adversarial Examples in Network Intrusion Detection SystemsCode1
Multi-Stage Optimized Machine Learning Framework for Network Intrusion Detection—0
EagerNet: Early Predictions of Neural Networks for Computationally Efficient Intrusion DetectionCode0
Efficient Deep CNN-BiLSTM Model for Network Intrusion DetectionCode1
Evaluating and Improving Adversarial Robustness of Machine Learning-Based Network Intrusion DetectorsCode1
Adversarial Machine Learning in Network Intrusion Detection Systems—0
A New Intrusion Detection System using the Improved Dendritic Cell Algorithm—0
LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput ApplicationsCode1
Hybrid Model For Intrusion Detection Systems—0
1D CNN Based Network Intrusion Detection with Normalization on Imbalanced Data—0
AnomalyDAE: Dual autoencoder for anomaly detection on attributed networksCode1
Survey of Network Intrusion Detection Methods from the Perspective of the Knowledge Discovery in Databases Process—0
Pelican: A Deep Residual Network for Network Intrusion Detection—0
Synthesis of a Machine Learning Model for Detecting Computer Attacks Based on the CICIDS2017 DatasetCode0
A Robust Comparison of the KDDCup99 and NSL-KDD IoT Network Intrusion Detection Datasets Through Various Machine Learning Algorithms—0
Network Intrusion Detection based on LSTM and Feature Embedding—0
Domain Knowledge Aided Explainable Artificial Intelligence for Intrusion Detection and Response—0
Deep Anomaly Detection with Deviation NetworksCode0
Intrusion Detection using Sequential Hybrid Model—0
ASNM Datasets: A Collection of Network Traffic Features for Testing of Adversarial Classifiers and Network Intrusion Detectors—0
WOTBoost: Weighted Oversampling Technique in Boosting for imbalanced learning—0
LuNet: A Deep Neural Network for Network Intrusion DetectionCode0
A Transfer Learning Approach for Network Intrusion Detection—0
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