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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
A Study on Transferability of Deep Learning Models for Network Intrusion DetectionCode1
CAGN-GAT Fusion: A Hybrid Contrastive Attentive Graph Neural Network for Network Intrusion DetectionCode1
TSI-GAN: Unsupervised Time Series Anomaly Detection using Convolutional Cycle-Consistent Generative Adversarial NetworksCode1
Applying Self-supervised Learning to Network Intrusion Detection for Network Flows with Graph Neural NetworkCode1
A flow-based IDS using Machine Learning in eBPFCode1
Bridging the gap to real-world for network intrusion detection systems with data-centric approachCode1
Problem space structural adversarial attacks for Network Intrusion Detection Systems based on Graph Neural NetworksCode1
SoK: Pragmatic Assessment of Machine Learning for Network Intrusion DetectionCode1
FlowTransformer: A Transformer Framework for Flow-based Network Intrusion Detection SystemsCode1
Edge-Detect: Edge-centric Network Intrusion Detection using Deep Neural NetworkCode1
Enhancing Robustness Against Adversarial Examples in Network Intrusion Detection SystemsCode1
IoTGeM: Generalizable Models for Behaviour-Based IoT Attack DetectionCode1
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly DetectionCode1
NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly GenerationCode1
Adaptive Intrusion Detection in the Networking of Large-Scale LANs with Segmented Federated LearningCode1
Evaluating and Improving Adversarial Robustness of Machine Learning-Based Network Intrusion DetectorsCode1
Representation Learning for Content-Sensitive Anomaly Detection in Industrial NetworksCode1
Continual Learning with Strategic Selection and Forgetting for Network Intrusion DetectionCode1
XG-NID: Dual-Modality Network Intrusion Detection using a Heterogeneous Graph Neural Network and Large Language ModelCode1
FedMSE: Federated learning for IoT network intrusion detectionCode1
Efficient Deep CNN-BiLSTM Model for Network Intrusion DetectionCode1
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoTCode1
PolyLUT-Add: FPGA-based LUT Inference with Wide InputsCode1
Unveiling the potential of Graph Neural Networks for robust Intrusion DetectionCode1
Improving Transferability of Network Intrusion Detection in a Federated Learning SetupCode1
Intrusion Detection with Segmented Federated Learning for Large-Scale Multiple LANsCode1
LiPar: A Lightweight Parallel Learning Model for Practical In-Vehicle Network Intrusion DetectionCode1
On the Cross-Dataset Generalization of Machine Learning for Network Intrusion DetectionCode1
LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput ApplicationsCode1
netFound: Foundation Model for Network SecurityCode1
An Intrusion Detection System based on Deep Belief NetworksCode1
Anomal-E: A Self-Supervised Network Intrusion Detection System based on Graph Neural NetworksCode1
PolyLUT: Learning Piecewise Polynomials for Ultra-Low Latency FPGA LUT-based InferenceCode1
AnomalyDAE: Dual autoencoder for anomaly detection on attributed networksCode1
Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier DetectionCode0
Large Language Models for Cyber Security: A Systematic Literature ReviewCode0
Hybrid Isolation Forest - Application to Intrusion DetectionCode0
Evaluating the Potential of Quantum Machine Learning in Cybersecurity: A Case-Study on PCA-based Intrusion Detection SystemsCode0
Implementing Lightweight Intrusion Detection System on Resource Constrained DevicesCode0
Kitsune: An Ensemble of Autoencoders for Online Network Intrusion DetectionCode0
A Robust PPO-optimized Tabular Transformer Framework for Intrusion Detection in Industrial IoT SystemsCode0
EagerNet: Early Predictions of Neural Networks for Computationally Efficient Intrusion DetectionCode0
Are Existing Out-Of-Distribution Techniques Suitable for Network Intrusion Detection?Code0
Enhanced Convolution Neural Network with Optimized Pooling and Hyperparameter Tuning for Network Intrusion DetectionCode0
Deep Q-Learning based Reinforcement Learning Approach for Network Intrusion DetectionCode0
Detection of Adversarial Training Examples in Poisoning Attacks through Anomaly DetectionCode0
A Novel Multi-Stage Approach for Hierarchical Intrusion DetectionCode0
A Comprehensive Comparative Study of Individual ML Models and Ensemble Strategies for Network Intrusion Detection SystemsCode0
Deep Learning Applications for Intrusion Detection in Network TrafficCode0
Diffusion-based Adversarial Purification for Intrusion DetectionCode0
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