MeritRank: Sybil Tolerant Reputation for Merit-based Tokenomics

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)
9 Downloads (Pure)

Abstract

Decentralized reputation schemes present a promising area of experimentation in blockchain applications. These solutions aim to overcome the shortcomings of simple monetary incentive mechanisms of naive tokenomics. However, there is a significant research gap regarding the limitations and benefits of such solutions. We formulate these trade-offs as a conjecture on the irreconcilability of three desirable properties of the reputation system in this context. Such a system can not be simultaneously generalizable, trustless, and Sybil resistant. To handle the limitations of this trilemma, we propose MeritRank: Sybil tolerant feedback aggregation mechanism for reputation. Instead of preventing Sybil attacks, our approach successfully bounds the benefits of these attacks. Using a dataset of participants’ interactions in MakerDAO, we run experiments to demonstrate Sybil tolerance of MeritRank. Decay parameters of reputation in MeritRank: transitivity decay and connectivity decay, allow for a fine-tuning of desirable levels of reputation utility and Sybil tolerance in different use contexts.
Original languageEnglish
Title of host publicationProceedings of the 2022 4th Conference on Blockchain Research & Applications for Innovative Networks and Services (BRAINS)
Place of PublicationDanvers
PublisherIEEE
Pages95-102
Number of pages8
ISBN (Electronic)978-1-6654-7158-9
ISBN (Print)978-1-6654-7159-6
DOIs
Publication statusPublished - 2022
Event2022 4th Conference on Blockchain Research & Applications for Innovative Networks and Services (BRAINS) - Paris, France
Duration: 27 Sept 202230 Sept 2022
Conference number: 4th

Publication series

Name2022 4th Conference on Blockchain Research and Applications for Innovative Networks and Services, BRAINS 2022

Conference

Conference2022 4th Conference on Blockchain Research & Applications for Innovative Networks and Services (BRAINS)
Country/TerritoryFrance
CityParis
Period27/09/2230/09/22

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Reputation
  • Sybil attack
  • Tokenomics
  • Feedback Aggregation

Fingerprint

Dive into the research topics of 'MeritRank: Sybil Tolerant Reputation for Merit-based Tokenomics'. Together they form a unique fingerprint.

Cite this