Publication | Closed Access
HyCC
64
Citations
43
References
2018
Year
Unknown Venue
Hardware SecuritySecure Multi-party ComputationEngineeringProgram AnalysisMpc ProtocolsCompiler TechnologyCompiler SupportComputer EngineeringFormal MethodsComputer ArchitectureParallel ProgrammingComputer ScienceSecure ComputingParallel ComputingOptimizing CompilerFormal VerificationCcs 2017Cryptography
While secure multi-party computation (MPC) is a vibrant research topic and a multitude of practical MPC applications have been presented recently, their development is still a tedious task that requires expert knowledge. Previous works have made first steps in compiling high-level descriptions from various source descriptions into MPC protocols, but only looked at a limited set of protocols. In this work we present HyCC, a tool-chain for automated compilation of ANSI C programs into hybrid protocols that efficiently and securely combine multiple MPC protocols with optimizing compilation, scheduling, and partitioning. As a result, our compiled protocols are able to achieve performance numbers that are comparable to hand-built solutions. For the MiniONN neural network (Liu et al., CCS 2017), our compiler improves performance of the resulting protocol by more than a factor of $3$. Thus, for the first time, highly efficient hybrid MPC becomes accessible for developers without cryptographic background.
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