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cs.CR2025
Federated Learning in the Wild: A Comparative Study for Cybersecurity under Non-IID and Unbalanced Settings
Roberto Doriguzzi-Corin, Petr Sabel, Silvio Cretti +1
Machine Learning (ML) techniques have shown strong potential for network traffic analysis; however, their effectiveness depends on access to representative, up-to-date datasets, wh…
cs.NI2025★ 4 cited
Disruption-aware Microservice Re-orchestration for Cost-efficient Multi-cloud Deployments
Marco Zambianco, Silvio Cretti, Domenico Siracusa
Multi-cloud environments enable a cost-efficient scaling of cloud-native applications across geographically distributed virtual nodes with different pricing models. In this context…