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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 176–200 of 261 papers

TitleStatusHype
Cybersecurity Anomaly Detection in Adversarial Environments—0
Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT—0
Benchmarking the Benchmark -- Analysis of Synthetic NIDS Datasets—0
Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-based Network Intrusion Detection—0
Supervised Feature Selection Techniques in Network Intrusion Detection: a Critical Review—0
Exploring Edge TPU for Network Intrusion Detection in IoT—0
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoTCode1
Explaining Network Intrusion Detection System Using Explainable AI Framework—0
TANTRA: Timing-Based Adversarial Network Traffic Reshaping Attack—0
A flow-based IDS using Machine Learning in eBPFCode1
Edge-Detect: Edge-centric Network Intrusion Detection using Deep Neural NetworkCode1
Federated Intrusion Detection for IoT with Heterogeneous Cohort Privacy—0
Intrusion detection in IoT using artificial neural networks on UNSW-15 dataset—0
Towards Network Traffic Monitoring Using Deep Transfer Learning—0
A Novel Resampling Technique for Imbalanced Dataset Optimization—0
A Comprehensive Guide to CAN IDS Data & Introduction of the ROAD Dataset—0
RNNIDS: Enhancing Network Intrusion Detection Systems through Deep Learning—0
Adaptive Intrusion Detection in the Networking of Large-Scale LANs with Segmented Federated LearningCode1
Review: Deep Learning Methods for Cybersecurity and Intrusion Detection Systems—0
Adversarial Examples in Constrained Domains—0
DualNet: Locate Then Detect Effective Payload with Deep Attention Network—0
Spiking Neural Networks with Single-Spike Temporal-Coded Neurons for Network Intrusion Detection—0
The Effective Methods for Intrusion Detection With Limited Network Attack Data: Multi-Task Learning and Oversampling—0
Intrusion Detection with Segmented Federated Learning for Large-Scale Multiple LANsCode1
Machine Learning Applications in Misuse and Anomaly Detection—0
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