Open Set Recognition for Malware Traffic via Predictive Uncertainty

Open Set Recognition for Malware Traffic via Predictive Uncertainty

Existing machine learning-based malware traffic recognition techniques can effectively detect abnormal behaviors in the network. However, almost all of them focus on a closed-set scenario in which the data used for training and testing come from the same label space. Since sophisticated malware and...

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Bibliographic Details
Main Authors: Xue Li, Jinlong Fei, Jiangtao Xie, Ding Li, Heng Jiang, Ruonan Wang, Zan Qi
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Electronics
Subjects:
machine learning
malware traffic recognition
open-set
predictive uncertainty
Online Access:https://www.mdpi.com/2079-9292/12/2/323

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