4 papers · 1 filter
Computationally Differentially Private Inner Product Protocols Imply Oblivious Transfer
Iftach Haitner, Noam Mazor, Jad Silbak +2
In distributed differential privacy, multiple parties collaborate to analyze their combined data while each party protects the confidentiality of its data from the others. Interest…
Differentially Private Quasi-Concave Optimization: Bypassing the Lower Bound and Application to Geometric Problems
Kobbi Nissim, Eliad Tsfadia, Chao Yan
We study the sample complexity of differentially private optimization of quasi-concave functions. For a fixed input domain , Cohen et al. (STOC 2023) proved that any g…
Data Reconstruction: When You See It and When You Don't
Edith Cohen, Haim Kaplan, Yishay Mansour +4
We revisit the fundamental question of formally defining what constitutes a reconstruction attack. While often clear from the context, our exploration reveals that a precise defini…
Smooth Lower Bounds for Differentially Private Algorithms via Padding-and-Permuting Fingerprinting Codes
Naty Peter, Eliad Tsfadia, Jonathan Ullman
Fingerprinting arguments, first introduced by Bun, Ullman, and Vadhan (STOC 2014), are the most widely used method for establishing lower bounds on the sample complexity or error o…