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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
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
Zero-day DDoS Attack Detection—0
1D CNN Based Network Intrusion Detection with Normalization on Imbalanced Data—0
A Combination of Temporal Sequence Learning and Data Description for Anomaly-based NIDS—0
Active Learning for Network Intrusion Detection—0
A Cyber Threat Intelligence Sharing Scheme based on Federated Learning for Network Intrusion Detection—0
A Deep Belief Network Based Machine Learning System for Risky Host Detection—0
A Defensive Framework Against Adversarial Attacks on Machine Learning-Based Network Intrusion Detection Systems—0
A Dependable Hybrid Machine Learning Model for Network Intrusion Detection—0
A Dual-Tier Adaptive One-Class Classification IDS for Emerging Cyberthreats—0
Integrating Graph Neural Networks with Scattering Transform for Anomaly Detection—0
Adv-Bot: Realistic Adversarial Botnet Attacks against Network Intrusion Detection Systems—0
Adversarial Evasion Attacks Practicality in Networks: Testing the Impact of Dynamic Learning—0
Adversarial Examples in Constrained Domains—0
Adversarial Machine Learning in Network Intrusion Detection Systems—0
Adversarial Machine Learning In Network Intrusion Detection Domain: A Systematic Review—0
A Grassmannian Approach to Zero-Shot Learning for Network Intrusion Detection—0
A Hypergraph-Based Machine Learning Ensemble Network Intrusion Detection System—0
An Adversarial Robustness Benchmark for Enterprise Network Intrusion Detection—0
Analyzing and Storing Network Intrusion Detection Data using Bayesian Coresets: A Preliminary Study in Offline and Streaming Settings—0
An AutoML-based approach for Network Intrusion Detection—0
Building an Efficient Intrusion Detection System Based on Feature Selection and Ensemble Classifier—0
A Network Intrusions Detection System based on a Quantum Bio Inspired Algorithm—0
A New Intrusion Detection System using the Improved Dendritic Cell Algorithm—0
A new semi-supervised inductive transfer learning framework: Co-Transfer—0
Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-based Network Intrusion Detection—0
An incremental hybrid adaptive network-based IDS in Software Defined Networks to detect stealth attacks—0
An Interpretable Federated Learning-based Network Intrusion Detection Framework—0
Anomaly based network intrusion detection for IoT attacks using deep learning technique—0
Cybersecurity Anomaly Detection in Adversarial Environments—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
A Novel Resampling Technique for Imbalanced Dataset Optimization—0
Are We There Yet? Unraveling the State-of-the-Art Graph Network Intrusion Detection Systems—0
Security Evaluation of Pattern Classifiers under Attack—0
Segmented Federated Learning for Adaptive Intrusion Detection System—0
Sequential Binary Classification for Intrusion Detection—0
SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network Intrusion Detection—0
Sorting out typicality with the inverse moment matrix SOS polynomial—0
Spiking Neural Networks with Single-Spike Temporal-Coded Neurons for Network Intrusion Detection—0
Statistical Detection of Adversarial examples in Blockchain-based Federated Forest In-vehicle Network Intrusion Detection Systems—0
Strengthening Network Intrusion Detection in IoT Environments with Self-Supervised Learning and Few Shot Learning—0
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
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
TANTRA: Timing-Based Adversarial Network Traffic Reshaping Attack—0
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