3 papers
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.CR2025
Adaptive Federated Learning with Functional Encryption: A Comparison of Classical and Quantum-safe Options
Enrico Sorbera, Federica Zanetti, Giacomo Brandi +3
Federated Learning (FL) is a collaborative method for training machine learning models while preserving the confidentiality of the participants' training data. Nevertheless, FL is…
cs.CV2025
Spotting tell-tale visual artifacts in face swapping videos: strengths and pitfalls of CNN detectors
Riccardo Ziglio, Cecilia Pasquini, Silvio Ranise
Face swapping manipulations in video streams represents an increasing threat in remote video communications, due to advances in automated and real-time tools. Recent literature pro…