SaTC: TTP: Small: Experimental Platform for Rapid Prototyping and Deployment of Secure Multi-Party Protocols

Suny At Buffalo, Amherst NY

Investigators

Abstract

The goal of this transition-to-practice project is to build an experimental platform for prototyping and deployment of secure multi-party computation applications. Secure multi-party computation is a concept that permits computing on private data distributed across different data sources by protecting the data via cryptographic means throughout the computation and thus conducting the computational task without learning the data. A variety of different techniques and tools have been developed in the past for secure computation with private data, but their deployment remains slow due to complexity of the techniques, a lack of sufficient expertise in organizations, and poor usability of the available tools. This project facilitates easier development and deployment of secure multi-party computation applications developed by application designers. This goal is accomplished by improving and extending a general-purpose secure multi-party computation compiler called PICCO. The resulting platform can be used by both researchers and programmers who are not domain experts. One of the primary features of the developed platform is the generality of the computation it supports. Namely, a program written in a variant of a conventional programming language is transformed into an implementation of the corresponding secure multi-party computation protocol and additional supporting programs. The platform is extensible and configurable to the needs of specific applications and their computational setup. A novel component includes a convenient web-based user interface for private data entry and output recovery generated at the time of program compilation. A part of the effort also consists of developing educational materials for facilitating the use of secure computation in courses and educational programs and helping local non-profit organizations set up and run privacy-preserving data analysis. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.