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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 1–50 of 261 papers

TitleStatusHype
TSI-GAN: Unsupervised Time Series Anomaly Detection using Convolutional Cycle-Consistent Generative Adversarial NetworksCode1
Edge-Detect: Edge-centric Network Intrusion Detection using Deep Neural NetworkCode1
FlowTransformer: A Transformer Framework for Flow-based Network Intrusion Detection SystemsCode1
SoK: Pragmatic Assessment of Machine Learning for Network Intrusion DetectionCode1
NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly GenerationCode1
Efficient Deep CNN-BiLSTM Model for Network Intrusion DetectionCode1
Continual Learning with Strategic Selection and Forgetting for Network Intrusion DetectionCode1
FedMSE: Federated learning for IoT network intrusion detectionCode1
netFound: Foundation Model for Network SecurityCode1
Representation Learning for Content-Sensitive Anomaly Detection in Industrial NetworksCode1
Unveiling the potential of Graph Neural Networks for robust Intrusion DetectionCode1
On the Cross-Dataset Generalization of Machine Learning for Network Intrusion DetectionCode1
Intrusion Detection with Segmented Federated Learning for Large-Scale Multiple LANsCode1
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly DetectionCode1
Adaptive Intrusion Detection in the Networking of Large-Scale LANs with Segmented Federated LearningCode1
CAGN-GAT Fusion: A Hybrid Contrastive Attentive Graph Neural Network for Network Intrusion DetectionCode1
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoTCode1
Enhancing Robustness Against Adversarial Examples in Network Intrusion Detection SystemsCode1
IoTGeM: Generalizable Models for Behaviour-Based IoT Attack DetectionCode1
LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput ApplicationsCode1
PolyLUT-Add: FPGA-based LUT Inference with Wide InputsCode1
Problem space structural adversarial attacks for Network Intrusion Detection Systems based on Graph Neural NetworksCode1
A Study on Transferability of Deep Learning Models for Network Intrusion DetectionCode1
XG-NID: Dual-Modality Network Intrusion Detection using a Heterogeneous Graph Neural Network and Large Language ModelCode1
Evaluating and Improving Adversarial Robustness of Machine Learning-Based Network Intrusion DetectorsCode1
PolyLUT: Learning Piecewise Polynomials for Ultra-Low Latency FPGA LUT-based InferenceCode1
Applying Self-supervised Learning to Network Intrusion Detection for Network Flows with Graph Neural NetworkCode1
LiPar: A Lightweight Parallel Learning Model for Practical In-Vehicle Network Intrusion DetectionCode1
Improving Transferability of Network Intrusion Detection in a Federated Learning SetupCode1
A flow-based IDS using Machine Learning in eBPFCode1
An Intrusion Detection System based on Deep Belief NetworksCode1
Anomal-E: A Self-Supervised Network Intrusion Detection System based on Graph Neural NetworksCode1
Bridging the gap to real-world for network intrusion detection systems with data-centric approachCode1
AnomalyDAE: Dual autoencoder for anomaly detection on attributed networksCode1
An Interpretable Federated Learning-based Network Intrusion Detection Framework—0
An incremental hybrid adaptive network-based IDS in Software Defined Networks to detect stealth attacks—0
Adversarial Evasion Attacks Practicality in Networks: Testing the Impact of Dynamic Learning—0
Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-based Network Intrusion Detection—0
A new semi-supervised inductive transfer learning framework: Co-Transfer—0
Adv-Bot: Realistic Adversarial Botnet Attacks against Network Intrusion Detection Systems—0
A Cyber Threat Intelligence Sharing Scheme based on Federated Learning for Network Intrusion Detection—0
A New Intrusion Detection System using the Improved Dendritic Cell Algorithm—0
A Network Intrusions Detection System based on a Quantum Bio Inspired Algorithm—0
Integrating Graph Neural Networks with Scattering Transform for Anomaly Detection—0
Building an Efficient Intrusion Detection System Based on Feature Selection and Ensemble Classifier—0
Assessing Cyclostationary Malware Detection via Feature Selection and Classification—0
ASNM Datasets: A Collection of Network Traffic Features for Testing of Adversarial Classifiers and Network Intrusion Detectors—0
An AutoML-based approach for Network Intrusion Detection—0
A Dual-Tier Adaptive One-Class Classification IDS for Emerging Cyberthreats—0
Active Learning for Network Intrusion Detection—0
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