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cs.CR2026
On the Impact of Entropy-based Features
Iuri Mundstock, Abreu Quevedo, Jéferson Campos Nobre +3
Network anomaly detection is increasingly challenging due to the growing diversity and variability of traffic patterns, which are not always well captured by traditional statistica…
cs.CR2024
Federated Learning under Attack: Improving Gradient Inversion for Batch of Images
Luiz Leite, Yuri Santo, Bruno L. Dalmazo +1
Federated Learning (FL) has emerged as a machine learning approach able to preserve the privacy of user's data. Applying FL, clients train machine learning models on a local datase…