Secure Multi-Party Computation (MPC) is a set of cryptographic techniques that allow for generating functionality for federated databases without the need to copy the data to a central database. Conceptually the functionality works as if the data were in a central database, while the cryptographic measures ensure data confidentiality. In the context of AI research, MPC is often employed to enable machine learning on federated databases with high levels of confidentiallity.


The TNO MPC Lab is a cross-project initiative initiated to improve the overall quality, generality, and reusability in the development of secure Multi-Party Computation solutions developed in the numerous (past, ongoing, and future) TNO projects that involve MPC. It consists of generic software components, procedures, and functionalities developed and maintained on a regular basis to facilitate and aid in the development of MPC solutions. The lab strives to boost the development of new protocols and solutions, and decrease time-to-market.

More information on the TNO MPC Lab can be found on
Open source publications on MPC are found on


Various TNO projects are related to Multi-Party Computation, for details on those see below. For more information about MPC, have a look here: