114 citations · 272 across the 20 of their papers we have counts for
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Scaling Compute Is Not All You Need for Adversarial Robustness
Edoardo Debenedetti, Zishen Wan, Maksym Andriushchenko +3
The last six years have witnessed significant progress in adversarially robust deep learning. As evidenced by the CIFAR-10 dataset category in RobustBench benchmark, the accuracy u…
Privacy Side Channels in Machine Learning Systems
Edoardo Debenedetti, Giorgio Severi, Nicholas Carlini +5
Most current approaches for protecting privacy in machine learning (ML) assume that models exist in a vacuum. Yet, in reality, these models are part of larger systems that include…
Evading Black-box Classifiers Without Breaking Eggs
Edoardo Debenedetti, Nicholas Carlini, Florian Tramèr
Decision-based evasion attacks repeatedly query a black-box classifier to generate adversarial examples. Prior work measures the cost of such attacks by the total number of queries…