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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 101–150 of 261 papers

TitleStatusHype
Efficient Network Representation for GNN-based Intrusion Detection—0
EG-ConMix: An Intrusion Detection Method based on Graph Contrastive Learning—0
A Network Intrusions Detection System based on a Quantum Bio Inspired Algorithm—0
Energy-based Models for Video Anomaly Detection—0
Towards Adversarial Realism and Robust Learning for IoT Intrusion Detection and Classification—0
Building an Efficient Intrusion Detection System Based on Feature Selection and Ensemble Classifier—0
Enhancing Trustworthiness in ML-Based Network Intrusion Detection with Uncertainty Quantification—0
Ensemble Classifier Design Tuned to Dataset Characteristics for Network Intrusion Detection—0
EPASAD: Ellipsoid decision boundary based Process-Aware Stealthy Attack Detector—0
Evaluating Generative Models for Tabular Data: Novel Metrics and Benchmarking—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
Explaining Network Intrusion Detection System Using Explainable AI Framework—0
Explaining Tree Model Decisions in Natural Language for Network Intrusion Detection—0
Explanation Method for Anomaly Detection on Mixed Numerical and Categorical Spaces—0
Exploring Edge TPU for Network Intrusion Detection in IoT—0
Extreme bandits—0
Feature Analysis for Machine Learning-based IoT Intrusion Detection—0
Feature Distribution Shift Mitigation with Contrastive Pretraining for Intrusion Detection—0
Feature Extraction for Machine Learning-based Intrusion Detection in IoT Networks—0
Feature Selection-based Intrusion Detection System Using Genetic Whale Optimization Algorithm and Sample-based Classification—0
Feature Selection for Network Intrusion Detection—0
FedDef: Defense Against Gradient Leakage in Federated Learning-based Network Intrusion Detection Systems—0
Federated Intrusion Detection for IoT with Heterogeneous Cohort Privacy—0
An AutoML-based approach for Network Intrusion Detection—0
Flow Exporter Impact on Intelligent Intrusion Detection Systems—0
"Flow Size Difference" Can Make a Difference: Detecting Malicious TCP Network Flows Based on Benford's Law—0
Analyzing and Storing Network Intrusion Detection Data using Bayesian Coresets: A Preliminary Study in Offline and Streaming Settings—0
From Zero-Shot Machine Learning to Zero-Day Attack Detection—0
Generative Active Adaptation for Drifting and Imbalanced Network Intrusion Detection—0
Generative AI-in-the-loop: Integrating LLMs and GPTs into the Next Generation Networks—0
Give and Take: Federated Transfer Learning for Industrial IoT Network Intrusion Detection—0
GowFed -- A novel Federated Network Intrusion Detection System—0
Graph-Powered Defense: Controller Area Network Intrusion Detection for Unmanned Aerial Vehicles—0
Heterogeneous Domain Adaptation for IoT Intrusion Detection: A Geometric Graph Alignment Approach—0
Host-Based Network Intrusion Detection via Feature Flattening and Two-stage Collaborative Classifier—0
Towards Network Traffic Monitoring Using Deep Transfer 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
1D CNN Based Network Intrusion Detection with Normalization on Imbalanced Data—0
Improving the Reliability of Network Intrusion Detection Systems through Dataset Integration—0
An Adversarial Robustness Benchmark for Enterprise Network Intrusion Detection—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
A Hypergraph-Based Machine Learning Ensemble Network Intrusion Detection System—0
Investigating Application of Deep Neural Networks in Intrusion Detection System Design—0
A Grassmannian Approach to Zero-Shot Learning for Network Intrusion Detection—0
KiNETGAN: Enabling Distributed Network Intrusion Detection through Knowledge-Infused Synthetic Data Generation—0
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