Last week, the Cybernetica research reports series continued with a new report focusing on methods for secure multiparty computation. The report, authored by Sander Siim and Dan Bogdanov, explores practical approaches for implementing complex privacy-preserving computational protocols more efficiently. Their work builds on Cybernetica's long-term research and experience in privacy-preserving computation technology.
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.
Read the full report: