4 citations · 6 across the 4 of their papers we have counts for
4 papers
Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization
Giuseppe Floris, Raffaele Mura, Luca Scionis +4
Evaluating the adversarial robustness of machine learning models using gradient-based attacks is challenging. In this work, we show that hyperparameter optimization can improve fas…
Samples on Thin Ice: Re-Evaluating Adversarial Pruning of Neural Networks
Giorgio Piras, Maura Pintor, Ambra Demontis +1
Neural network pruning has shown to be an effective technique for reducing the network size, trading desirable properties like generalization and robustness to adversarial attacks…
Adversarial Attacks Against Uncertainty Quantification
Emanuele Ledda, Daniele Angioni, Giorgio Piras +3
Machine-learning models can be fooled by adversarial examples, i.e., carefully-crafted input perturbations that force models to output wrong predictions. While uncertainty quantifi…
Explaining Machine Learning DGA Detectors from DNS Traffic Data
Giorgio Piras, Maura Pintor, Luca Demetrio +1
One of the most common causes of lack of continuity of online systems stems from a widely popular Cyber Attack known as Distributed Denial of Service (DDoS), in which a network of…