Symphony: Expressive Secure Multiparty Computation with Coordination. Ian Sweet, David Darais, David Heath, Ryan Estes, Bill Harris, and Michael Hicks, June 2022.

Secure Multiparty Computation (MPC) refers to a family of cryptographic techniques with which mutually untrusting parties may compute arbitrary functions of their private inputs while revealing only the function output. MPC has broad application, but it can be hard to program MPCs correctly and efficiently, especially when they require coordinating disparate computational roles. We present Symphony, a new functional programming language for MPC whose programs can easily coordinate many parties, and whose first-class shares and first-class party sets provide unmatched language-level expressive power. Symphony generalizes the single-instruction, multiple-data (SIMD) semantics of prior MPC languages, and using a core language called , we prove that this intuitive, generalized SIMD view of a program coincides with its actual distributed semantics. Thus the programmer can reason about her programs by reading them from top to bottom, even though in reality the program runs distributed across many machines. We implemented a prototype interpreter for Symphony and with it wrote a variety of MPC programs, finding that it can express optimized protocols that other languages cannot. We also measured the performance of the interpreter on several benchmark programs. Despite Symphony's added expressiveness, we find its performance is competitive with Obliv-C, a state-of-the-art two-party MPC framework for C .

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@misc{sweet22symphony,
  title = {Symphony: Expressive Secure Multiparty Computation with Coordination},
  author = {Ian Sweet and David Darais and David Heath and Ryan Estes and Bill Harris and Michael Hicks},
  month = jun,
  year = 2022
}

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