37 citations · 57 across the 5 of their papers we have counts for
5 papers
DP-Cryptography: Marrying Differential Privacy and Cryptography in Emerging Applications
Sameer Wagh, Xi He, Ashwin Machanavajjhala +1
Differential privacy (DP) has arisen as the state-of-the-art metric for quantifying individual privacy when sensitive data are analyzed, and it is starting to see practical deploym…
FALCON: Honest-Majority Maliciously Secure Framework for Private Deep Learning
Sameer Wagh, Shruti Tople, Fabrice Benhamouda +3
We propose Falcon, an end-to-end 3-party protocol for efficient private training and inference of large machine learning models. Falcon presents four main advantages - (i) It is hi…
Towards Probabilistic Verification of Machine Unlearning
David Marco Sommer, Liwei Song, Sameer Wagh +1
The right to be forgotten, also known as the right to erasure, is the right of individuals to have their data erased from an entity storing it. The status of this long held notion…
The Pyramid Scheme: Oblivious RAM for Trusted Processors
Manuel Costa, Lawrence Esswood, Olga Ohrimenko +2
Modern processors, e.g., Intel SGX, allow applications to isolate secret code and data in encrypted memory regions called enclaves. While encryption effectively hides the contents…
Differentially Private Oblivious RAM
Sameer Wagh, Paul Cuff, Prateek Mittal
In this work, we investigate if statistical privacy can enhance the performance of ORAM mechanisms while providing rigorous privacy guarantees. We propose a formal and rigorous fra…