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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 51–100 of 261 papers

TitleStatusHype
SAFE: Self-Supervised Anomaly Detection Framework for Intrusion Detection—0
Detecting APT Malware Command and Control over HTTP(S) Using Contextual Summaries—0
Technical Report: Generating the WEB-IDS23 Dataset—0
Investigating Application of Deep Neural Networks in Intrusion Detection System Design—0
PolyLUT: Ultra-low Latency Polynomial Inference with Hardware-Aware Structured Pruning—0
A Comparative Analysis of DNN-based White-Box Explainable AI Methods in Network SecurityCode0
Learning in Multiple Spaces: Few-Shot Network Attack Detection with Metric-Fused Prototypical Networks—0
A Temporal Convolutional Network-based Approach for Network Intrusion Detection—0
Flow Exporter Impact on Intelligent Intrusion Detection Systems—0
PyOD 2: A Python Library for Outlier Detection with LLM-powered Model SelectionCode0
Convolutional Neural Networks and Mixture of Experts for Intrusion Detection in 5G Networks and beyond—0
Graph-Powered Defense: Controller Area Network Intrusion Detection for Unmanned Aerial Vehicles—0
An AutoML-based approach for Network Intrusion Detection—0
Feature Selection for Network Intrusion Detection—0
Take Package as Language: Anomaly Detection Using TransformerCode0
Intelligent Green Efficiency for Intrusion Detection—0
SCGNet-Stacked Convolution with Gated Recurrent Unit Network for Cyber Network Intrusion Detection and Intrusion Type ClassificationCode0
Implementing Lightweight Intrusion Detection System on Resource Constrained DevicesCode0
NIDS Neural Networks Using Sliding Time Window Data Processing with Trainable Activations and its Generalization Capability—0
A Comprehensive Comparative Study of Individual ML Models and Ensemble Strategies for Network Intrusion Detection SystemsCode0
XAI-based Feature Selection for Improved Network Intrusion Detection SystemsCode0
Transforming In-Vehicle Network Intrusion Detection: VAE-based Knowledge Distillation Meets Explainable AI—0
Data Distribution ValuationCode0
Enhanced Convolution Neural Network with Optimized Pooling and Hyperparameter Tuning for Network Intrusion DetectionCode0
A Survey for Deep Reinforcement Learning Based Network Intrusion Detection—0
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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