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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 76–100 of 261 papers

TitleStatusHype
TEAM: Temporal Adversarial Examples Attack Model against Network Intrusion Detection System Applied to RNN—0
A Novel Perturb-ability Score to Mitigate Evasion Adversarial Attacks on Flow-Based ML-NIDS—0
Systematic Evaluation of Synthetic Data Augmentation for Multi-class NetFlow Traffic—0
Towards Explainable Network Intrusion Detection using Large Language Models—0
Multi-agent Reinforcement Learning-based Network Intrusion Detection System—0
Diffusion-based Adversarial Purification for Intrusion DetectionCode0
PPT-GNN: A Practical Pre-Trained Spatio-Temporal Graph Neural Network for Network Security—0
Detection-Rate-Emphasized Multi-objective Evolutionary Feature Selection for Network Intrusion Detection—0
Sequential Binary Classification for Intrusion Detection—0
Generative AI-in-the-loop: Integrating LLMs and GPTs into the Next Generation Networks—0
Strengthening Network Intrusion Detection in IoT Environments with Self-Supervised Learning and Few Shot Learning—0
A Synergistic Approach In Network Intrusion Detection By Neurosymbolic AI—0
KiNETGAN: Enabling Distributed Network Intrusion Detection through Knowledge-Infused Synthetic Data Generation—0
Practical Performance of a Distributed Processing Framework for Machine-Learning-based NIDS—0
Large Language Models in Wireless Application Design: In-Context Learning-enhanced Automatic Network Intrusion Detection—0
Large Language Models for Cyber Security: A Systematic Literature ReviewCode0
Feature Distribution Shift Mitigation with Contrastive Pretraining for Intrusion Detection—0
Integrating Graph Neural Networks with Scattering Transform for Anomaly Detection—0
An incremental hybrid adaptive network-based IDS in Software Defined Networks to detect stealth attacks—0
Dealing with Imbalanced Classes in Bot-IoT Dataset—0
EG-ConMix: An Intrusion Detection Method based on Graph Contrastive Learning—0
A Dual-Tier Adaptive One-Class Classification IDS for Emerging Cyberthreats—0
An Adversarial Robustness Benchmark for Enterprise Network Intrusion Detection—0
Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction—0
Deep Learning Applications for Intrusion Detection in Network TrafficCode0
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