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"Muu" projekt MSHZU12009R
MSHZU12009R "UaESMC - Kasutajasõbralikud ja kiired turvalised ühisarvutused (1.02.2012−31.07.2015)", Pille Pruulmann-Vengerfeldt, Tartu Ülikool, Tartu Ülikool, Sotsiaal- ja haridusteaduskond, Ajakirjanduse, kommunikatsiooni- ja infoteaduste instituut.
MSHZU12009R
UaESMC - Kasutajasõbralikud ja kiired turvalised ühisarvutused
UaESMC - Usable and Efficient Secure Multiparty Computation
UaESMC - Usable and Efficient Secure Multiparty Computation
1.02.2012
31.07.2015
Teadus- ja arendusprojekt
Muu
ETIS klassifikaatorAlamvaldkondCERCS klassifikaatorFrascati Manual’i klassifikaatorProtsent
4. Loodusteadused ja tehnika4.6. ArvutiteadusedP170 Arvutiteadus, arvutusmeetodid, süsteemid, juhtimine (automaatjuhtimisteooria)1.1. Matemaatika ja arvutiteadus (matemaatika ja teised sellega seotud teadused: arvutiteadus ja sellega seotud teadused (ainult tarkvaraarendus, riistvara arendus kuulub tehnikavaldkonda)100,0
AsutusRiikTüüp
Euroopa Komisjon
PerioodSumma
01.02.2012−31.07.2015109 000,00 EUR
109 000,00 EUR
7.raamprogramm

In this project, we will bring the techniques and tools for Secure Multiparty Computation (SMC) to a level where they can be applied to decisional and computational pröblems of practical size in several different social and economic sectors. To achieve this, we will apply a multi-pronged research effort to build the theoretical foundations for the practical aspects of SMC application. Our project will combine the identification of a representative set of computational problems, the development of appropriate cryptographic and other tools for solving those probiems in a privacy-preserving manner, the study of incentives of various parties to participate in privacy-preserving computations, and the exploration of practical limits and trade-offs in the deployment of SMC solutions. All these research areas will be explored in tight cooperation, as advances in any of them will shift priorities in all other areas. Through the integrated effort we hope to build a framework that allows us to place any multiparty computation problem in the appropriate context and to see whether and how the privacy issues in this problem can be mitigated. While cryptographic techniques for SMC have been studied before in Europe, our quest for identifying the other enablers of SMC through an integrated research effort appears to be novel. We believe that the research activities structured in this manner will in the fastest possible way bring us closer to our long-term goal of the privacy requirements of the input data of a computation notbeing a consideration whetherto perform it.
In this project, we will bring the techniques and tools for Secure Multiparty Computation (SMC) to a level where they can be applied to decisional and computational pröblems of practical size in several different social and economic sectors. To achieve this, we will apply a multi-pronged research effort to build the theoretical foundations for the practical aspects of SMC application. Our project will combine the identification of a representative set of computational problems, the development of appropriate cryptographic and other tools for solving those probiems in a privacy-preserving manner, the study of incentives of various parties to participate in privacy-preserving computations, and the exploration of practical limits and trade-offs in the deployment of SMC solutions. All these research areas will be explored in tight cooperation, as advances in any of them will shift priorities in all other areas. Through the integrated effort we hope to build a framework that allows us to place any multiparty computation problem in the appropriate context and to see whether and how the privacy issues in this problem can be mitigated. While cryptographic techniques for SMC have been studied before in Europe, our quest for identifying the other enablers of SMC through an integrated research effort appears to be novel. We believe that the research activities structured in this manner will in the fastest possible way bring us closer to our long-term goal of the privacy requirements of the input data of a computation notbeing a consideration whetherto perform it.
KirjeldusProtsent
Alusuuring75,0
Rakendusuuring25,0