108 citations · 191 across the 8 of their papers we have counts for
4 papers · 1 filter
Reconstructing Training Data with Informed Adversaries
Borja Balle, Giovanni Cherubin, Jamie Hayes
Given access to a machine learning model, can an adversary reconstruct the model's training data? This work studies this question from the lens of a powerful informed adversary who…
Bayes Security: A Not So Average Metric
Konstantinos Chatzikokolakis, Giovanni Cherubin, Catuscia Palamidessi +1
Security system designers favor worst-case security metrics, such as those derived from differential privacy (DP), due to the strong guarantees they provide. On the downside, these…
F-BLEAU: Fast Black-box Leakage Estimation
Giovanni Cherubin, Konstantinos Chatzikokolakis, Catuscia Palamidessi
We consider the problem of measuring how much a system reveals about its secret inputs. We work under the black-box setting: we assume no prior knowledge of the system's internals,…
Bayes, not Naïve: Security Bounds on Website Fingerprinting Defenses
Giovanni Cherubin
Website Fingerprinting (WF) attacks raise major concerns about users' privacy. They employ Machine Learning (ML) to allow a local passive adversary to uncover the Web browsing beha…