Gossip-based aggregation of trust in decentralized reputation systems

Yoram Bachrach, Ariel Parnes, Ariel D. Procaccia, Jeffrey S. Rosenschein

Research output: Contribution to journalArticlepeer-review

26 Scopus citations


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, a global perspective, and simplicity. We demonstrate that our scheme motivates agents to maintain a very high reputation, by showing that the higher an agent's reputation is above the threshold set by its peers, the more transactions it would be able to complete within a certain time unit. We analyze the relation between the amount by which an agent's average reputation exceeds the threshold and the time required to close a deal. This analysis is carried out both theoretically, and empirically through a simulation system called GossipTrustSim. Finally, we show that our approach is inherently impervious to certain kinds of attacks.

Original languageAmerican English
Pages (from-to)153-172
Number of pages20
JournalAutonomous Agents and Multi-Agent Systems
Issue number2
StatePublished - Oct 2009

Bibliographical note

Funding Information:
Acknowledgments This work was partially supported by Israel Science Foundation grant #898/05. The work was done while Ariel Procaccia was at the Hebrew University of Jerusalem, and was supported by the Adams Fellowship Program of the Israel Academy of Sciences and Humanities.


  • Game theory
  • Gossip
  • Manipulation
  • Reputation systems
  • Trust


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