On the use of feedback 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 (i) consent to being connected through introduction via a third node and (ii) provide binary-valued feedback about one another to that introducer when the connection closes. This paper models probabilistically the decision processes by which this feedback is both generated and interpreted-the associated reputation management algorithms account for different modes of misbehavior, respect the inherent information decentralization and are consistent with the utility-maximizing decisions established previously for other parts of the protocol.