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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 241–250 of 261 papers

TitleStatusHype
A Robust Comparison of the KDDCup99 and NSL-KDD IoT Network Intrusion Detection Datasets Through Various Machine Learning Algorithms—0
TEAM: Temporal Adversarial Examples Attack Model against Network Intrusion Detection System Applied to RNN—0
ASNM Datasets: A Collection of Network Traffic Features for Testing of Adversarial Classifiers and Network Intrusion Detectors—0
Assessing Cyclostationary Malware Detection via Feature Selection and Classification—0
Anomaly based network intrusion detection for IoT attacks using deep learning technique—0
A Survey for Deep Reinforcement Learning Based Network Intrusion Detection—0
A Synergistic Approach In Network Intrusion Detection By Neurosymbolic AI—0
Technical Report: Generating the WEB-IDS23 Dataset—0
A Temporal Convolutional Network-based Approach for Network Intrusion Detection—0
A Transfer Learning Approach for Network Intrusion Detection—0
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