Last week, the Cybernetica research reports series continued with a report discussing methods of secure multiparty computation. The report by Sander Siim and Dan Bogdanov describes how complex privacy-preserving computational protocols could be implemented with less effort. The report is based on Cybernetica's long-term research on privacy-preserving computations.
Using the method described in the report, computations described in an ordinary high-level programming language can be transformed directly into protocols that work on secret-shared data. This enables highly complex protocols to be built easily for computing platforms based on secret sharing. The proposed solution has been prototyped on Sharemind, a privacy-preserving database and application platform developed by Cybernetica.
The research report can be read here.