Privacy-preserving auction using multi-party computation (II)

Abstract

This report aims to investigate and evaluate the practicality and performance of privacy-preserving auction using multi-party computation. This investigation consists of two main phases. We first develop an infrastructure where the multi-party computation can be carried out. Next, we experiment with a multi-party computation (MPC) algorithm we develop to determine the feasibility. In the experiment, we tweak the parameters and record the corresponding performance of the auction. With the data collected, we gained insights in helping developers with designing their MPC Algorithm. This helps us demonstrate and determine the probable use case for multi-party computation.