21 citations · 56 across the 11 of their papers we have counts for
4 papers · 1 filter
Exploiting Edge Features for Transferable Adversarial Attacks in Distributed Machine Learning
Giulio Rossolini, Fabio Brau, Alessandro Biondi +2
As machine learning models become increasingly deployed across the edge of internet of things environments, a partitioned deep learning paradigm in which models are split across mu…
Robust-by-Design Classification via Unitary-Gradient Neural Networks
Fabio Brau, Giulio Rossolini, Alessandro Biondi +1
The use of neural networks in safety-critical systems requires safe and robust models, due to the existence of adversarial attacks. Knowing the minimal adversarial perturbation of…
On the Minimal Adversarial Perturbation for Deep Neural Networks with Provable Estimation Error
Fabio Brau, Giulio Rossolini, Alessandro Biondi +1
Although Deep Neural Networks (DNNs) have shown incredible performance in perceptive and control tasks, several trustworthy issues are still open. One of the most discussed topics…
Increasing the Confidence of Deep Neural Networks by Coverage Analysis
Giulio Rossolini, Alessandro Biondi, Giorgio Buttazzo
The great performance of machine learning algorithms and deep neural networks in several perception and control tasks is pushing the industry to adopt such technologies in safety-c…