Optimizing Secure Function Evaluation on Mobile Devices
Benjamin Mood
Committee: Kevin Butler (chair), Michal Young
Masters Thesis(May 2024)
Keywords:

Secure function evaluation (SFE) on mobile devices, such as smartphones, allows for the creation of new privacy-preserving applications. Generating the circuits on smartphones which allow for executing customized functions, however, is infeasible for most problems due to memory constraints. In this thesis, we develop a new methodology for generating circuits that is memory-efficient. Using the standard SFDL language for describing secure functions as input, we design a new pseudo- assembly language (PAL) and a template-driven compiler, generating circuits which can be evaluated with the canonical Fairplay evaluation framework. We deploy this compiler and demonstrate larger circuits can now be generated on smartphones. We show our compiler’s ability to interface with other execution systems and perform optimizations on that execution system. We show how runtime generation of circuits can be used in practice. Our results demonstrate the feasibility of generating garbled circuits on mobile devices.

This thesis includes previously published co-authored material.