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Lightweight Federated Learning Based Detection of Malicious Activity in Distributed Networks
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2023
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Gesellschaft für Informatik e.V.
Zusammenfassung
In an increasingly complex cyber threat landscape, traditional malware detection methods often fall short, particularly within resource-limited distributed networks like smart grids. This research project aims to develop an efficient malware detection system for such distributed networks, focusing on three elements: feature extraction, feature selection, and classification. For classification, a lightweight and accurate machine-learning model needs to be developed.