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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
Supervised Feature Selection Techniques in Network Intrusion Detection: a Critical Review—0
Survey of Network Intrusion Detection Methods from the Perspective of the Knowledge Discovery in Databases Process—0
SynGAN: Towards Generating Synthetic Network Attacks using GANs—0
V-CNN: When Convolutional Neural Network encounters Data Visualization—0
WeiDetect: Weibull Distribution-Based Defense against Poisoning Attacks in Federated Learning for Network Intrusion Detection Systems—0
Systematic Evaluation of Synthetic Data Augmentation for Multi-class NetFlow Traffic—0
TAD: Transfer Learning-based Multi-Adversarial Detection of Evasion Attacks against Network Intrusion Detection Systems—0
Anomaly Detection via Minimum Likelihood Generative Adversarial Networks—0
A Novel Approach To Network Intrusion Detection System Using Deep Learning For Sdn: Futuristic Approach—0
A Novel Deep Learning based Model to Defend Network Intrusion Detection System against Adversarial Attacks—0
WOTBoost: Weighted Oversampling Technique in Boosting for imbalanced learning—0
A Novel Resampling Technique for Imbalanced Dataset Optimization—0
Cybersecurity Anomaly Detection in Adversarial Environments—0
TANTRA: Timing-Based Adversarial Network Traffic Reshaping Attack—0
Are We There Yet? Unraveling the State-of-the-Art Graph Network Intrusion Detection Systems—0
A Robust Comparison of the KDDCup99 and NSL-KDD IoT Network Intrusion Detection Datasets Through Various Machine Learning Algorithms—0
TEAM: Temporal Adversarial Examples Attack Model against Network Intrusion Detection System Applied to RNN—0
ASNM Datasets: A Collection of Network Traffic Features for Testing of Adversarial Classifiers and Network Intrusion Detectors—0
Assessing Cyclostationary Malware Detection via Feature Selection and Classification—0
Anomaly based network intrusion detection for IoT attacks using deep learning technique—0
A Survey for Deep Reinforcement Learning Based Network Intrusion Detection—0
A Synergistic Approach In Network Intrusion Detection By Neurosymbolic AI—0
Technical Report: Generating the WEB-IDS23 Dataset—0
A Temporal Convolutional Network-based Approach for Network Intrusion Detection—0
A Transfer Learning Approach for Network Intrusion Detection—0
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