15 citations · 19 across the 5 of their papers we have counts for
9 papers
Distributed Point Functions and Function Secret Sharing
Elette Boyle, Niv Gilboa, Yuval Ishai +1
A distributed point function (DPF) is a cryptographic primitive that enables compressed additive sharing of a secret weight-1 vector (equivalently, a point function) across two or…
Fast Bounded-Independence Functions and Their Duals
Martijn Brehm, Yuval Ishai, Nicolas Resch
We continue the study of {\em fast} functions, computable by linear-size circuits, that share useful properties of random functions. Motivated by cryptographic applications, we gen…
Bounded Simultaneous Messages
Andrej Bogdanov, Krishnamoorthy Dinesh, Yuval Filmus +3
We consider the following question of bounded simultaneous messages (BSM) protocols: Can computationally unbounded Alice and Bob evaluate a function of their inputs by sen…
Locality-Preserving Hashing for Shifts with Connections to Cryptography
Elette Boyle, Itai Dinur, Niv Gilboa +3
Can we sense our location in an unfamiliar environment by taking a sublinear-size sample of our surroundings? Can we efficiently encrypt a message that only someone physically clos…
On the Download Rate of Homomorphic Secret Sharing
Ingerid Fosli, Yuval Ishai, Victor I. Kolobov +1
A homomorphic secret sharing (HSS) scheme is a secret sharing scheme that supports evaluating functions on shared secrets by means of a local mapping from input shares to output sh…
Function Secret Sharing for PSI-CA:With Applications to Private Contact Tracing
Samuel Dittmer, Yuval Ishai, Steve Lu +5
In this work we describe a token-based solution to Contact Tracing via Distributed Point Functions (DPF) and, more generally, Function Secret Sharing (FSS). The key idea behind the…
Lightweight Techniques for Private Heavy Hitters
Dan Boneh, Elette Boyle, Henry Corrigan-Gibbs +2
This paper presents Poplar, a new system for solving the private heavy-hitters problem. In this problem, there are many clients and a small set of data-collection servers. Each cli…
Outsourcing Private Machine Learning via Lightweight Secure Arithmetic Computation
Siddharth Garg, Zahra Ghodsi, Carmit Hazay +3
In several settings of practical interest, two parties seek to collaboratively perform inference on their private data using a public machine learning model. For instance, several…
Secure Arithmetic Computation with No Honest Majority
Yuval Ishai, Manoj Prabhakaran, Amit Sahai
We study the complexity of securely evaluating arithmetic circuits over finite rings. This question is motivated by natural secure computation tasks. Focusing mainly on the case of…