Enabling Privacy-Preserving Cyber Threat Detection with Federated Learning

Despite achieving good performance and wide adoption, machine learning based security detection models (e.g., malware classifiers) are subject to concept drift and evasive evolution of attackers, which renders up-to-date threat data as a necessity. However, due to enforcement of various privacy prot...

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Bibliographic Details
Main Authors Bi, Yu, Li, Yekai, Feng, Xuan, Mi, Xianghang
Format Journal Article
LanguageEnglish
Published 07.04.2024
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