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cs.LG2026
End-to-End Verifiable and Robust Federated Learning
Doryan Lesaignoux, Enrique Mármol Campos, Gabriele Spini +2
Federated learning enables multiple parties to train a shared model without centralizing raw data with the help of an aggregator, but introduces integrity risks once participants o…
cs.CR2026
ICS Cybersecurity Datasets: A Systematic Meta-Review of Coverage, Evaluation Practice, and Structural Gaps
Konstantinos E. Kampourakis, Vyron Kampourakis, Georgios Kambourakis +4
Intrusion detection research in Industrial Control Systems (ICS) heavily depends on public datasets, yet no prior work has systematically assessed whether the collective dataset co…