We study differential privacy in a distributed setting where two parties would like to perform analysis of their joint data while preserving privacy for both datasets. Our results ...
Andrew McGregor, Ilya Mironov, Toniann Pitassi, Om...
Differential privacy has gained a lot of attention in recent years as a general model for the protection of personal information when used and disclosed for secondary purposes. It...
Data privacy has been an important research topic in the security, theory and database communities in the last few decades. However, many existing studies have restrictive assumpt...
Private matching between datasets owned by distinct parties is a challenging problem with several applications. Private matching allows two parties to identify the records that ar...
Ali Inan, Murat Kantarcioglu, Gabriel Ghinita, Eli...
We study the role that privacy-preserving algorithms, which prevent the leakage of specific information about participants, can play in the design of mechanisms for strategic age...