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F. Schleif

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#machine learning Preprint Sep 2026

Federated Attack Campaign Detection via Contrastive Encoding of Threat Indicators in Gradient Updates

FedIoC is contributed as a modular framework in which clients fold locally available structured threat indicators into their gradient updates, and is used to pinpoint the non-IID gradient structure as the main driver of recovery and to define the open problem of designing encoders that improve on it.

Manuel Röder, Bibin Babu, F. Schleif · 0 citations

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