SEP 4, 2026 · PREPRINT
Federated Attack Campaign Detection via Contrastive Encoding of Threat Indicators in Gradient Updates
arXiv
This is a methods paper presenting a novel federated learning framework for cyberattack detection, evaluated on public benchmarks without clinical outcomes, real-world deployment data, or comparison to established detection systems.
Study details
DesignAlgorithmic framework with benchmark evalua…
InterventionFedIoC: federated learning framework in whi…