Gossip-Based Aggregation Of Trust In Decentralized Reputation Systems

Abstract

Decentralized Reputation Systems have recently emerged as a prominent method of establishing trust among self-interested agents in online environments. A key issue is the efficient aggregation of data in the system; several approaches have been proposed, but they are plagued by major shortcomings. We put forward a novel, decentralized data management scheme grounded in gossip-based algorithms. Rumor mongering is known to possess algorithmic advantages, and indeed, our framework inherits many of their salient features: scalability, robustness, globality, and simplicity. We also demonstrate that our scheme motivates agents to maintain a sparkling clean reputation, and is inherently impervious to certain kinds of attacks.