Network traffic anomaly detection model based on feature grouping and multi‐autoencoders integration

Network traffic anomaly detection model based on feature grouping and multi‐autoencoders integration

Abstract This paper presents a network traffic anomaly detection model based on feature grouping and multiple autoencoders (multi‐AEs) integration. This model comprises four modules: feature grouping module, feature learning module, AUC and optimal threshold calculation module, and anomaly detection...

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Bibliographic Details
Main Authors: Yang Zhou, Haoyang Zeng, Zhourong Zheng, Wei Zhang
Format: Article
Language:English
Published: Wiley 2024-12-01
Series:Electronics Letters
Subjects:
computer network security
learning (artificial intelligence)
Online Access:https://doi.org/10.1049/ell2.70103
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https://doi.org/10.1049/ell2.70103

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