ARM2GC: Succinct Garbled Processor for Secure Computation

We present ARM2GC, a novel secure computation framework based on Yao's Garbled Circuit (GC) protocol and the ARM processor. It allows users to develop privacy-preserving applications using standard high-level programming languages (e.g., C) and compile them using off-the-shelf ARM compilers (e.g., gcc-arm). The main enabler of this framework is the introduction of SkipGate, an algorithm that dynamically omits the communication and encryption cost of the gates whose outputs are independent of the private data. SkipGate greatly enhances the performance of ARM2GC by omitting costs of the gates associated with the instructions of the compiled binary, which is known by both parties involved in the computation. Our evaluation on benchmark functions demonstrates that ARM2GC not only outperforms the current GC frameworks that support high-level languages, it also achieves efficiency comparable to the best prior solutions based on hardware description languages. Moreover, in contrast to previous high-level frameworks with domain-specific languages and customized compilers, ARM2GC relies on standard ARM compiler which is rigorously verified and supports programs written in the standard syntax.Comment: 13 page

MPCircuits: Optimized Circuit Generation for Secure Multi-Party Computation

Secure Multi-party Computation (MPC) is one of the most influential achievements of modern cryptography: it allows evaluation of an arbitrary function on private inputs from multiple parties without revealing the inputs. A crucial step of utilizing contemporary MPC protocols is to describe the function as a Boolean circuit. While efficient solutions have been proposed for special case of two-party secure computation, the general case of more than two-party is not addressed. This paper proposes MPCircuits, the first automated solution to devise the optimized Boolean circuit representation for any MPC function using hardware synthesis tools with new customized libraries that are scalable to multiple parties. MPCircuits creates a new end-to-end tool-chain to facilitate practical scalable MPC realization. To illustrate the practicality of MPCircuits, we design and implement a set of five circuits that represent real-world MPC problems. Our benchmarks inherently have different computational and communication complexities and are good candidates to evaluate MPC protocols. We also formalize the metrics by which a given protocol can be analyzed. We provide extensive experimental evaluations for these benchmarks; two of which are the first reported solutions in multi-party settings. As our experimental results indicate, MPCircuits reduces the computation time of MPC protocols by up to 4.2x