On privacy preference in collusion-deterrence games for secure multi-party computation

Abstract

Secure multi-party computation (MPC) has been established as the de facto paradigm for protecting privacy in distributed computation. Information-theoretic secure MPC protocols, though more efficient than their computationally secure counterparts, require at least three computational parties and are prone to collusion attacks. Previous work has used mechanism designs to deter collusion. An important element missing is the consideration of how different players value privacy. In this paper, we provide a detailed analysis of possible outcomes under different privacy preferences based on the relative cost of collusion attacks over loss of privacy. We explicitly calculate the conditions under which honesty is the solution. Simulation results provide further evidence to demonstrate the validity of our mechanism design.