Doreen Riepel
Doreen Riepel
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Highly-Effective Backdoors for Hash Functions and Beyond
We study the possibility of schemes whose public parameters have been generated along with a backdoor. We consider the goal of the …
Mihir Bellare
,
Doreen Riepel
,
Laura Shea
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Verifiable and Provably Secure Machine Unlearning
Machine unlearning aims to remove points from the training dataset of a machine learning model after training; for example when a user …
Thorsten Eisenhofer
,
Doreen Riepel
,
Varun Chandrasekaran
,
Esha Ghosh
,
Olga Ohrimenko
,
Nicolas Papernot
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