Anomaly based Resilient Network Intrusion Detection using Inferential Autoencoders

This article focuses on the application of conditional variational autoencoders as anomaly detectors to identify emerging threats in computer networks. Autoencoders are machine learning techniques that are used to find lower-dimensional representations, i.e. an encoding in latent space, from input s...

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Veröffentlicht in:	2021 IEEE International Conference on Cyber Security and Resilience (CSR) S. 1 - 7
Hauptverfasser:	Hannan, Abdul, Gruhl, Christian, Sick, Bernhard
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 26.07.2021
Schlagworte:	Anomaly Detection Artificial Intelligence Autoencoders Computer networks Cyber Security Encoding Network Intrusion Detection Probability distribution Resilience Robustness Telecommunication traffic Training data Turning Variational Autoencoders
Online-Zugang:	Volltext
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