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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Bibliographic Details

Published in:	2021 IEEE International Conference on Cyber Security and Resilience (CSR) pp. 1 - 7
Main Authors:	Hannan, Abdul, Gruhl, Christian, Sick, Bernhard
Format:	Conference Proceeding
Language:	English
Published:	IEEE 26.07.2021
Subjects:	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 Access:	Get full text
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