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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 71–80 of 261 papers

TitleStatusHype
Adversarial Evasion Attacks Practicality in Networks: Testing the Impact of Dynamic Learning—0
Bayesian Hyperparameter Optimization for Deep Neural Network-Based Network Intrusion Detection—0
Unsupervised Network Intrusion Detection System for AVTP in Automotive Ethernet Networks—0
Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-based Network Intrusion Detection—0
A Virtual Cybersecurity Department for Securing Digital Twins in Water Distribution Systems—0
Attribute Learning for 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 Transfer Learning Approach for Network Intrusion Detection—0
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