Private Computation Framework 2.0

Abstract

This paper explores advancements in the open-source library, Private Computation Framework, that significantly improve the resource usage and application development lifecycle of Multi-Party Compute applications. First we elaborate on the architecture of Private Computation Framework. We then discuss implementation XOR Secret-Sharing-Based MPC protocols and how it improves upon previous usage of Garbled Circuits, to provide the same privacy guarantees while significantly reducing network usage. The paper also explores new standard libraries provided by the framework, additional optimizations in the latest release of Private Computation Framework, and future development opportunities.

Project page available here: https://github.com/facebookresearch/fbpcf.

Latest Publications

Sustainable AI: Environmental Implications, Challenges and Opportunities

Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, Gloria Chang, Fiona Aga Behram, James Huang, Charles Bai, Michael Gschwind, Anurag Gupta, Myle Ott, Anastasia Melnikov, Salvatore Candido, David Brooks, Geeta Chauhan, Benjamin Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Max Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim Hazelwood

MLSys - 2022