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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 226–250 of 261 papers

TitleStatusHype
SynGAN: Towards Generating Synthetic Network Attacks using GANs—0
Sparse Bayesian approach for metric learning in latent spaceCode0
Analyzing and Storing Network Intrusion Detection Data using Bayesian Coresets: A Preliminary Study in Offline and Streaming Settings—0
A Combination of Temporal Sequence Learning and Data Description for Anomaly-based NIDS—0
Mimic Learning to Generate a Shareable Network Intrusion Detection Model—0
Building an Efficient Intrusion Detection System Based on Feature Selection and Ensemble Classifier—0
Active Learning for Network Intrusion Detection—0
Rallying Adversarial Techniques against Deep Learning for Network Security—0
Deep Adversarial Learning in Intrusion Detection: A Data Augmentation Enhanced Framework—0
Use Dimensionality Reduction and SVM Methods to Increase the Penetration Rate of Computer Networks—0
Benchmarking datasets for Anomaly-based Network Intrusion Detection: KDD CUP 99 alternativesCode0
Evaluating Shallow and Deep Neural Networks for Network Intrusion Detection Systems in Cyber SecurityCode0
Anomaly Detection via Minimum Likelihood Generative Adversarial Networks—0
Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier DetectionCode0
V-CNN: When Convolutional Neural Network encounters Data Visualization—0
A Taxonomy of Network Threats and the Effect of Current Datasets on Intrusion Detection SystemsCode0
Onion-Peeling Outlier Detection in 2-D data Sets—0
Kitsune: An Ensemble of Autoencoders for Online Network Intrusion DetectionCode0
Detection of Adversarial Training Examples in Poisoning Attacks through Anomaly DetectionCode0
A Deep Belief Network Based Machine Learning System for Risky Host Detection—0
A Grassmannian Approach to Zero-Shot Learning for Network Intrusion Detection—0
Security Evaluation of Pattern Classifiers under Attack—0
Energy-based Models for Video Anomaly Detection—0
Model Selection for Anomaly Detection—0
Hybrid Isolation Forest - Application to Intrusion DetectionCode0
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