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SPEC

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Secure Private Efficient Multiparty Computation

MPC is a cryptographic technique that allows a set of mutually distrusting parties to compute any joint function of their private inputs in a way that preserves the confidentiality of the inputs and the correctness of the result.... ver más

31/10/2024

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

AARHUS UNIVERSITET No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

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Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2024-10-31

ERC-2018-STG: ERC Starting Grant

I+D

Cerrada hace 7 años

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

2 Participantes

1.50M€ | Lider

SOCIEDAD ANONIMA INDUSTRIAS...

749.96K€ | Participante

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Duración del proyecto: 74 meses Fecha Inicio: 2018-08-16
Fecha Fin: 2024-10-31

Líder del proyecto

AARHUS UNIVERSITET No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 1M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto MPC is a cryptographic technique that allows a set of mutually distrusting parties to compute any joint function of their private inputs in a way that preserves the confidentiality of the inputs and the correctness of the result. Examples of MPC applications include secure auctions, benchmarking, privacy-preserving data mining, etc. In the last decade, the efficiency of MPC has improved significantly, especially with respect to evaluating functions expressed as Boolean and arithmetic circuits. These advances have allowed several companies worldwide to implement and include MPC solutions in their products. Unfortunately, it now appears (and it’s partially confirmed by theoretical lower bounds) that we have reached a wall with respect to possible optimizations of current building blocks of MPC, which prevents MPC to be used in critical large-scale applications. I therefore believe that a radical paradigm-shift in MPC research is needed in order to make MPC truly practical. With this project, I intend to take a step back, challenge current assumptions in MPC research and design novel MPC solutions. My hypothesis is that taking MPC to the next level requires more realistic modelling of the way that security, privacy and efficiency are defined and measured. By combining classic MPC techniques with research in neighbouring areas of computer science I will fulfill the aim of the project and in particular: 1) Understand the limitations of current abstract models for MPC and refine them to more precisely capture real world requirements in terms of security, privacy and efficiency. 2) Use the new models to guide the developments of the next generation of MPC protocols, going beyond current performances and therefore enabling large-scale applications. 3) Investigate the necessary privacy-utility trade-offs that parties undertake when participating in distributed computations and define MPC functionalities that encourage cooperation for rational parties.

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