Using Self-Organizing Maps for the Behavioral Analysis of Virtualized Network Functions. - Giacomo Lanciano; Antonio Ritacco; Fabio Brau; Tommaso Cucinotta; Marco Vannucci; Antonino Artale; João Barata; Enrica Sposato (CLOSER (Selected Papers), 2020)

Forecasting Operation Metrics for Virtualized Network Functions. - Tommaso Cucinotta; Giacomo Lanciano; Antonio Ritacco; Fabio Brau; Filippo Galli; Vincenzo Iannino; Marco Vannucci; Antonino Artale; João Barata; Enrica Sposato (CCGRID, 2021)

Robust-by-Design Classification via Unitary-Gradient Neural Networks. - Fabio Brau; Giulio Rossolini; Alessandro Biondi 001; Giorgio C. Buttazzo (AAAI, 2023)

Defending from Physically-Realizable Adversarial Attacks through Internal Over-Activation Analysis. - Giulio Rossolini; Federico Nesti; Fabio Brau; Alessandro Biondi 001; Giorgio C. Buttazzo (AAAI, 2023)

On the Minimal Adversarial Perturbation for Deep Neural Networks With Provable Estimation Error. - Fabio Brau; Giulio Rossolini; Alessandro Biondi 001; Giorgio C. Buttazzo (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Maximizing team synergy in AI-related interdisciplinary groups: an interdisciplinary-by-design iterative methodology. - Piercosma Bisconti; Davide Orsitto; Federica Fedorczyk; Fabio Brau; Marianna Capasso; Lorenzo De Marinis; Hüseyin Eken; Federica Merenda; Mirko Forti; Marco Pacini; Claudia Schettini (AI Soc., 2023)

1-Lipschitz Layers Compared: Memory, Speed, and Certifiable Robustness. - Bernd Prach; Fabio Brau; Giorgio C. Buttazzo; Christoph H. Lampert (CVPR, 2024)

Video Deblurring by Sharpness Prior Detection and Edge Information. - Yang Tian; Fabio Brau; Giulio Rossolini; Giorgio C. Buttazzo; Hao Meng (CoRR, 2025)

Exploiting Edge Features for Transferable Adversarial Attacks in Distributed Machine Learning. - Giulio Rossolini; Fabio Brau; Alessandro Biondi 001; Battista Biggio; Giorgio C. Buttazzo (CoRR, 2025)