1 code implementation • 24 Feb 2024 • Federica Granese, Marco Romanelli, Pablo Piantanida
We approach this defensive strategy with utmost caution, operating in an environment where the defender possesses significantly less information compared to the attacker.
no code implementations • 4 Feb 2023 • Federica Granese, Marco Romanelli, Siddharth Garg, Pablo Piantanida
Multi-armed adversarial attacks, in which multiple algorithms and objective loss functions are simultaneously used at evaluation time, have been shown to be highly successful in fooling state-of-the-art adversarial examples detectors while requiring no specific side information about the detection mechanism.
1 code implementation • 30 Jun 2022 • Federica Granese, Marine Picot, Marco Romanelli, Francisco Messina, Pablo Piantanida
Detection of adversarial examples has been a hot topic in the last years due to its importance for safely deploying machine learning algorithms in critical applications.
1 code implementation • NeurIPS 2021 • Federica Granese, Marco Romanelli, Daniele Gorla, Catuscia Palamidessi, Pablo Piantanida
Deep neural networks (DNNs) have shown to perform very well on large scale object recognition problems and lead to widespread use for real-world applications, including situations where DNN are implemented as "black boxes".