Scalable Rational Secret Sharing

We consider the classical secret sharing problem in the case where all agents are selfish but rational. In recent work, Kol and Naor show that in the non-simultaneous communciation model (i.e. when rushing is possible), there is no Nash equilibrium that ensures all agents learn the secret. However, they describe a mechanism for this problem that is an epsilon-Nash equilibrium, i.e. it is close to an equilibrium in the sense that no player can gain more than utility by deviating from it. Unfortunately, the Kol and Naor mechanism, and, to the best of our knowledge; all previous mechanisms for this problem require each agent to send O(n) messages in expectation, where n is the number of agents. This may be problematic for some applications of rational secret sharing such as secure multiparty computation and simulation of a mediator. We address this issue by describing a mechanism for rational n-out-of-n secret sharing that is an epsilon-Nash equilibrium, and is scalable in the sense that it requires each agent to send only an expected O(1) bits. Moreover, the latency of our mechanism is O(log n) in expectation, compared to O(n) expected latency for the Kol and Naor result. We also design mechanisms for a relaxed variant of rational m-out-of-n secret sharing where m = circle minus(n) that require each processor to send O(log n) bits and have O(log n) latency. Our mechanisms are non-cryptographic, and are not susceptible to backwards induction.