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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 201–210 of 261 papers

TitleStatusHype
NIDS Neural Networks Using Sliding Time Window Data Processing with Trainable Activations and its Generalization Capability—0
One-Shot Learning on Attributed Sequences—0
On Generalisability of Machine Learning-based Network Intrusion Detection Systems—0
Onion-Peeling Outlier Detection in 2-D data Sets—0
On the Evaluation of Sequential Machine Learning for Network Intrusion Detection—0
On the (Statistical) Detection of Adversarial Examples—0
PacketCLIP: Multi-Modal Embedding of Network Traffic and Language for Cybersecurity Reasoning—0
Pelican: A Deep Residual Network for Network Intrusion Detection—0
Performance Comparison and Implementation of Bayesian Variants for Network Intrusion Detection—0
POET: A Self-learning Framework for PROFINET Industrial Operations Behaviour—0
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