Abstract

Secure Function Evaluation (SFE) has received recent attention due to the massive collection and mining of personal data, but remains impractical due to its large computational cost. Garbled Circuits (GC) is a protocol for implementing SFE which can evaluate any function that can be expressed as a Boolean circuit and obtain the result while keeping each party’s input private. Recent advances have led to a surge of garbled circuit implementations in software for a variety of different tasks. However, these implementations are inefficient, and therefore GC is not widely used, especially for large problems. This research investigates, implements, and evaluates secure computation generation using a heterogeneous computing platform featuring FPGAs. We have designed and implemented SIFO: secure computational infrastructure using FPGA overlays. Unlike traditional FPGA design, a coarse-grained overlay architecture is adopted which supports mapping SFE problems that are too large to map to a single FPGA. Host tools provided include SFE problem generator, parser, and automatic host code generation. Our design allows repurposing an FPGA to evaluate different SFE tasks without the need for reprogramming and fully explores the parallelism for any GC problem. Our system demonstrates an order of magnitude speedup compared with an existing software platform.

Highlights

  • We introduce the relevant background on garbled circuits, including terminology and techniques

  • For the hardware architecture on FPGA, our design uses a coarse-grained overlay architecture and enables the evaluation of different Secure Function Evaluation (SFE) tasks without the need for reprogramming. e host-side workflow includes garbled circuit generator, problem parser, and host code generation tools which can be configurable for different hardware architectures. ese tools explore the parallelism for any Garbled Circuits (GC) problem and generate the host program based on the structure of the problem

  • We provide analytical tools to show the different characteristics of a problem

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Summary

Introduction

We introduce the relevant background on garbled circuits, including terminology and techniques. Related work on garbled circuit implementations is discussed. Our research accelerates Secure Function Evaluation (SFE), Garbled Circuits (GC), using FPGAs. Our research accelerates Secure Function Evaluation (SFE), Garbled Circuits (GC), using FPGAs In this model, there are two or more users with data which they wish to keep private and a function to be evaluated over those data. All parties know the function being evaluated and learn the outcome of the evaluation, but users do not reveal their data. A canonical problem exemplifying SFE is the “Millionaires’ Problem:” two millionaires wish to know who is worth more without revealing their personal worth to each other

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