Evaluation of MPC’s State of the Art

Data holds the enormous potential to learn a lot from it and thus improve practically all areas of life. Especially when we combine data from different sources (e.g. organizations or individuals). One of the biggest challenges in such scenarios is to protect the privacy of individuals.

“(Secure) Multi-Party Computation (MPC) is a technology that can be used, among other things, to perform data analyses from various sources while maintaining the privacy of the individual data providers. On the one hand, MPC is being increasingly used in practice, mainly due to relatively-mature MPC engines and frameworks such as MP-SPDZ. On the other hand, the relatively-large development of the theoretical and practical aspects of MPC over the last two decades has led to numerous choices and requirements when using MPC in real-world applications.

For example, there exist several threat models in MPC. Further, also different MPC engines/frameworks and MPC protocols/computation models to choose from exist; depending on the use case and general requirements on MPC. This diversity can be an initial hurdle on the way to a smooth use of MPC in real scenarios. Therefore, this report looks at the state of the art of MPC. The focus is placed on the areas of computation paradigms and environmental parameters, MPC engines/frameworks, threat models, use cases, and MPC within as well as offered by companies. Finally, the general status of computation on encrypted data is considered. Further resources on MPC and secure computations on encrypted data in general are shown in the appendix.

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File	Description	File size
MPC-State-2023 (DE)		4 MB