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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 151–200 of 261 papers

TitleStatusHype
TEAM: Temporal Adversarial Examples Attack Model against Network Intrusion Detection System Applied to RNN—0
Technical Report: Generating the WEB-IDS23 Dataset—0
Temporal Analysis of NetFlow Datasets for Network Intrusion Detection Systems—0
The Effective Methods for Intrusion Detection With Limited Network Attack Data: Multi-Task Learning and Oversampling—0
The Efficacy of Transformer-based Adversarial Attacks in Security Domains—0
Threat analysis of IoT networks Using Artificial Neural Network Intrusion Detection System—0
TII-SSRC-23 Dataset: Typological Exploration of Diverse Traffic Patterns for Intrusion Detection—0
Towards Adversarial Realism and Robust Learning for IoT Intrusion Detection and Classification—0
Towards a Privacy-preserving Deep Learning-based Network Intrusion Detection in Data Distribution Services—0
Towards Explainable Network Intrusion Detection using Large Language Models—0
Towards Network Traffic Monitoring Using Deep Transfer Learning—0
Toward Supervised Anomaly Detection—0
Training a Bidirectional GAN-based One-Class Classifier for Network Intrusion Detection—0
Transforming In-Vehicle Network Intrusion Detection: VAE-based Knowledge Distillation Meets Explainable AI—0
Two-stage Deep Stacked Autoencoder with Shallow Learning for Network Intrusion Detection System—0
Untargeted White-box Adversarial Attack with Heuristic Defence Methods in Real-time Deep Learning based Network Intrusion Detection System—0
Use Dimensionality Reduction and SVM Methods to Increase the Penetration Rate of Computer Networks—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
WOTBoost: Weighted Oversampling Technique in Boosting for imbalanced learning—0
Hybrid Model For Intrusion Detection Systems—0
IGRF-RFE: A Hybrid Feature Selection Method for MLP-based Network Intrusion Detection on UNSW-NB15 Dataset—0
Improving the Reliability of Network Intrusion Detection Systems through Dataset Integration—0
Intelligent Green Efficiency for Intrusion Detection—0
A Novel Perturb-ability Score to Mitigate Evasion Adversarial Attacks on Flow-Based ML-NIDS—0
Intrusion detection in IoT using artificial neural networks on UNSW-15 dataset—0
Intrusion Detection using Sequential Hybrid Model—0
Investigating Application of Deep Neural Networks in Intrusion Detection System Design—0
KiNETGAN: Enabling Distributed Network Intrusion Detection through Knowledge-Infused Synthetic Data Generation—0
KnowML: Improving Generalization of ML-NIDS with Attack Knowledge Graphs—0
Large Language Models in Wireless Application Design: In-Context Learning-enhanced Automatic Network Intrusion Detection—0
Late Breaking Results: Scalable and Efficient Hyperdimensional Computing for Network Intrusion Detection—0
Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT—0
LBDMIDS: LSTM Based Deep Learning Model for Intrusion Detection Systems for IoT Networks—0
Learning in Multiple Spaces: Few-Shot Network Attack Detection with Metric-Fused Prototypical Networks—0
Learning Privately from Multiparty Data—0
Learning to Detect: A Data-driven Approach for Network Intrusion Detection—0
Machine Learning Applications in Misuse and Anomaly Detection—0
Machine Learning-Based Intrusion Detection: Feature Selection versus Feature Extraction—0
Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction—0
Mapping the Landscape of Generative AI in Network Monitoring and Management—0
Mimic Learning to Generate a Shareable Network Intrusion Detection Model—0
Model Selection for Anomaly Detection—0
Multi-agent Reinforcement Learning-based Network Intrusion Detection System—0
Multidomain transformer-based deep learning for early detection of network intrusion—0
Multi-Stage Optimized Machine Learning Framework for Network Intrusion Detection—0
NetSentry: A Deep Learning Approach to Detecting Incipient Large-scale Network Attacks—0
Network Intrusion Detection based on LSTM and Feature Embedding—0
Network Intrusion Detection System in a Light Bulb—0
Network Intrusion Detection Using Wrapper-based Decision Tree for Feature Selection—0
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