MP-SPDZ: A Versatile Framework for Multi-Party Computation

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While there is a growing number of MPC implementations, most of them are restricted in terms of protocols, security models, and applications. MP-SPDZ on the other hand offers more than 30 protocol variants in a range of security models and a programming interface that is application-independent. I will talk about the core design choices of MP-SPDZ and how they facilitate this versatility. In particular, the fact that almost all protocol feature two basic operations, some sort of addition and multiplication, provide a simple template for reusable code. I will also present recent results in privacy-preserving machine learning. We have implemented a network for MNIST with which we achieved an accuracy close to cleartext training with a few hours of training.

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