Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Jin, Jiankai"'
Autor:
Jin, Jiankai, Chuengsatiansup, Chitchanok, Murray, Toby, Rubinstein, Benjamin I. P., Yarom, Yuval, Ohrimenko, Olga
Current implementations of differentially-private (DP) systems either lack support to track the global privacy budget consumed on a dataset, or fail to faithfully maintain the state continuity of this budget. We show that failure to maintain a privac
Externí odkaz:
http://arxiv.org/abs/2401.17628
Adversarial examples pose a security risk as they can alter decisions of a machine learning classifier through slight input perturbations. Certified robustness has been proposed as a mitigation where given an input $\mathbf{x}$, a classifier returns
Externí odkaz:
http://arxiv.org/abs/2205.10159
Differential privacy is a de facto privacy framework that has seen adoption in practice via a number of mature software platforms. Implementation of differentially private (DP) mechanisms has to be done carefully to ensure end-to-end security guarant
Externí odkaz:
http://arxiv.org/abs/2112.05307