Aykurt, Fatih
Using secure multi-party computing protocols (MPC), a group of participants who distrust one another can securely compute any function of their shared secret inputs. Participants exchange these inputs in a manner similar to secret sharing, where each participant owns a portion of the input but is unable to independently reconstruct the complete information without collaborating with the other participants. This kind of computation is quite powerful and has many uses where data privacy is quite criti- cal such as areas like government, business, and academia. MPC has grown from a subject of theoretical study to a technology being employed in industry, becom- ing effective enough to be deployed in practice with various algorithms implemented with MPC frameworks. In this study, two versatile MPC frameworks, MP-SPDZ and MPyC are analyzed. These frameworks’ performances are compared by using algo- rithms execution times from basic operations to more complex structures like shuffle sort algorithm. Profiling results are also analyzed to reveal the bottleneck points of the algorithms where the time consumption increases drastically. To detect the critical parts easier, profiling results are visualized as dot graphs. Besides all these, in the MPyC framework, Sattolo shuffle algorithm is implemented and compared with the current modern version of Fisher-Yates algorithm
Citation Formats
F. Aykurt, “ANALYSIS OF TWO VERSATILE MPC FRAMEWORKS MP-SPDZ AND MPYC,” M.S. - Master of Science, Middle East Technical University, 2023.