On optimal decisions in an introduction-based reputation protocol

Consider a network environment with no central authority in which each node gains value when transacting with behaving nodes but risks losing value when transacting with misbehaving nodes. One recently proposed mechanism for curbing the harm by misbehaving nodes is that of an introduction-based reputation protocol [1]: transactions are permitted only between two nodes who consent to being connected through introduction via a third node. This paper models the main decision process in this protocol, namely that of continuing/closing an active connection, as a sequential detection problem in which each stage corresponds to a transaction that is (perhaps erroneously) classified as either benign or harmful. It is shown that the optimal decision takes the form of a reputation threshold policy, the exact threshold determined by a Bellman equation that admits a tractable iterative solution.