An End-to-End System for Large Scale P2P MPC-as-a-Service and Low-Bandwidth MPC for Weak Participants
Assi Barak, Martin Hirt, Lior Koskas, Yehuda Lindell
Abstract
Protocols for secure multiparty computation enable a set of parties to compute a joint function of their inputs, while preserving privacy, correctness and more. In theory, secure computation has broad applicability and can be used to solve many of the modern concerns around utilization of data and privacy. Huge steps have been made towards this vision in the past few years, and we now have protocols that can carry out large computations extremely efficiently, especially in the setting of an honest majority. However, in practice, there are still major barriers to widely deploying secure computation, especially in a decentralized manner. In this paper, we present the first end-to-end automated system for deploying largescale MPC protocols between end users, called MPSaaS (for MPC system-as-a-service). Our system enables parties to pre-enroll in an upcoming MPC computation, and then participate by either running software on a VM instance (e.g., in Amazon), or by running the protocol on a mobile app, in Javascript in their browser, or even on an IoT device. Our system includes an automation system for deploying MPC protocols, an administration component for setting up an MPC computation and inviting participants, and an end-user component for running the MPC protocol in realistic end-user environments. We demonstrate our system for a specific application of running secure polls and surveys, where the secure computation is run end-to-end with each party actually running the protocol (i.e., without relying on a set of servers to run the protocol for them). This is the first such system constructed, and is a big step forward to the goal of commoditizing MPC.
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Cited by top-tier papers8
- ABY2.0: Improved Mixed-Protocol Secure Two-Party ComputationArpita Patra, Thomas Schneider, Ajith Suresh, Hossein YalameUSENIX Security 2021 · 307 citations
- SoK: General Purpose Compilers for Secure Multi-Party ComputationMarcella Hastings, Brett Hemenway, Daniel Noble, Steve ZdancewicS&P 2019 · 181 citations
- zkay: Specifying and Enforcing Data Privacy in Smart ContractsSamuel Steffen, Benjamin Bichsel, Mario Gersbach, Noa Melchior et al.CCS 2019 · 82 citations
- Practical Fully Secure Three-Party Computation via Sublinear Distributed Zero-Knowledge ProofsElette Boyle, Niv Gilboa, Yuval Ishai, Ariel NofCCS 2019 · 71 citations
- Fast Fully Secure Multi-Party Computation over Any Ring with Two-Thirds Honest MajorityAnders P. K. Dalskov, Daniel Escudero, Ariel NofCCS 2022 · 17 citations
Builds on5
- MASCOT: Faster Malicious Arithmetic Secure Computation with Oblivious TransferMarcel Keller, Emmanuela Orsini, Peter SchollCCS 2016 · 487 citations
- High-Throughput Semi-Honest Secure Three-Party Computation with an Honest MajorityToshinori Araki, Jun Furukawa, Yehuda Lindell, Ariel Nof et al.CCS 2016 · 463 citations
- Optimized Honest-Majority MPC for Malicious Adversaries - Breaking the 1 Billion-Gate Per Second BarrierToshinori Araki, Assi Barak, Jun Furukawa, Tamar Lichter et al.S&P 2017 · 137 citations
- A Framework for Constructing Fast MPC over Arithmetic Circuits with Malicious Adversaries and an Honest-MajorityYehuda Lindell, Ariel NofCCS 2017 · 106 citations
- Constant Round Maliciously Secure 2PC with Function-independent Preprocessing using LEGOJesper Buus Nielsen, Thomas Schneider, Roberto TrifilettiNDSS 2017 · 57 citations
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