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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 161–170 of 261 papers

TitleStatusHype
Deep Q-Learning based Reinforcement Learning Approach for Network Intrusion DetectionCode0
A Cyber Threat Intelligence Sharing Scheme based on Federated Learning for Network Intrusion Detection—0
Bridging the gap to real-world for network intrusion detection systems with data-centric approachCode1
PWG-IDS: An Intrusion Detection Model for Solving Class Imbalance in IIoT Networks Using Generative Adversarial Networks—0
From Zero-Shot Machine Learning to Zero-Day Attack Detection—0
Feature Analysis for Machine Learning-based IoT Intrusion Detection—0
Feature Extraction for Machine Learning-based Intrusion Detection in IoT Networks—0
Learning to Detect: A Data-driven Approach for Network Intrusion Detection—0
A new semi-supervised inductive transfer learning framework: Co-Transfer—0
Unveiling the potential of Graph Neural Networks for robust Intrusion DetectionCode1
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