Pushing Secure Multi-Party Computation to Reality

Tuesday, March 13, 2018 -
4:00pm to 5:00pm
CS 1240

Speaker Name: 

Xiao Wang

Speaker Institution: 

University of Maryland



Cookies Location: 

CS 1240


Secure multi-party computation (MPC) is a powerful cryptographic tool
that allows users to perform privacy-preserving computations on their
collective data, without revealing anything about their data to each
other. For many decades MPC was considered infeasible, but recent
progress has made MPC significantly more practical to the point where
it is attracting interest from government agencies as well as start-up

I will survey the field of MPC, and then discuss my research aimed at
making this technique more efficient, more robust, more scalable, and
easier to use. In addition to new protocols, I will also describe EMP,
an open-source toolkit I have developed that allows non-experts to
apply MPC in real-world applications.

Xiao Wang is a Ph.D. student at the University of Maryland, where he
is advised by Professor Jonathan Katz. His research interests focus on
applied cryptography, specifically on designing efficient
privacy-preserving systems based on secure multi-party computation.
For this work, he has received a Best Paper Award in Applied Cyber
Security at CSAW 2015, an iDASH Competition Award in 2015, a Human
Longevity Inc. Award for MPC in 2016, and an ACM CCS Best Paper Award
in 2017.