Accessible and Scalable
Secure Multi-Party Computation

Researchers at Boston University, together with collaborators at several other institutions and organizations, are developing open-source libraries, frameworks, and systems that enable the implementation and deployment of applications that employ secure multi-party computation in accessible and scalable ways. This page contains links to recent publications and other relevant articles.

Please contact us if you would like to learn more or are interested in collaborating.

Libraries and Frameworks

  • JavaScript Implementation of Federated Functionalities (JIFF).
    JavaScript library for building web-based applications that employ secure multi-party computation (MPC).
  • Web-MPC.
    JavaScript application for user-friendly privacy-preserving web-based data aggregation use cases.
  • Conclave Workflow Manager.
    Query compiler that automatically optimizes relational queries to be executed under MPC by factoring it into (1) scalable, local, cleartext processing workflows (using backends such as Apache Spark) and (2) isolated MPC workflows that utilize existing MPC backend frameworks.

Publications and Reports

Talks and Presentations

Other News, Reports, and Coverage

Current and Past Collaborators

Faculty

Azer Bestavros
BU
Andrei Lapets
BU
Mayank Varia
BU
Ran Canetti
BU
Shannon Roberts
UMass

Researchers and Software Engineers

Frederick Jansen
BU
Lucy Qin
BU
Ben Getchell
BU
Nikolaj Volgushev
Alexandra Institute
Malte Schwarzkopf
MIT
Shreya Pandit
BU
San Tran
BU

Students

Kinan Dak Albab
BU
Rawane Issa
BU
Justin Chen
BU
Jacqueline You
BU
Mike Gajda
BU
Rose Kelly
UMass
Eric Dunton
BU
Kyle Holzinger
BU

Acknowledgments

This effort exists thanks to the support and cooperation of Boston University, including the Department of Computer Science, the Hariri Institute for Computing, the Software & Application Innovation Lab, the MACS project, the Mass Open Cloud, and the Initiative on Cities.

We also thank the City of Boston, the Boston Women's Workforce Council, and the Greater Boston Chamber of Commerce.

This work is partially supported by the National Science Foundation under Grants #1430145 (SCOPE), #1414119 (MACS), #1718135, and #1739000. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

This work is also supported in part by the Honda Research Institutes.