Improving Data Generalization With Variational Autoencoders for Network Traffic Anomaly Detection

Improving Data Generalization With Variational Autoencoders for Network Traffic Anomaly Detection

Deep generative models have increasingly become popular in different domains such as image processing, though, they hardly appear in the cybersecurity arena. While the main application of these models is dimensionality reduction, marginally they have been utilized for overcoming challenges such as d...

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Bibliographic Details
Main Authors: Mehrnoosh Monshizadeh, Vikramajeet Khatri, Marah Gamdou, Raimo Kantola, Zheng Yan
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Anomaly detection
data mining
feature selection
machine learning
security
Online Access:https://ieeexplore.ieee.org/document/9399440/

Internet

https://ieeexplore.ieee.org/document/9399440/

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