We argue that designing a system that “guarantees” the privacy of its information may not be enough. One must also consider the price for providing that protection: For exampl...
Many databases will not or can not be disclosed without strong guarantees that no sensitive information can be extracted. To address this concern several data perturbation techniq...
In this paper, we investigate privacy-preserving data imputation on distributed databases. We present a privacypreserving protocol for filling in missing values using a lazy deci...
In this work we provide efficient distributed protocols for generating shares of random noise, secure against malicious participants. The purpose of the noise generation is to crea...
Cynthia Dwork, Krishnaram Kenthapadi, Frank McSher...
Abstract. Analysis of privacy-sensitive data in a multi-party environment often assumes that the parties are well-behaved and they abide by the protocols. Parties compute whatever ...