Improving the Resiliency of Decentralized Crowdsourced Blockchain Oracles

Authors
Publication date 2023
Host editors
  • J. Mikyška
  • C. de Mulatier
  • M. Paszynski
  • V.V. Krzhizhanovskaya
  • J.J. Dongarra
  • P.M.A. Sloot
Book title Computational Science – ICCS 2023
Book subtitle 23rd International Conference, Prague, Czech Republic, July 3–5, 2023 : proceedings
ISBN
  • 9783031359941
ISBN (electronic)
  • 9783031359958
Series Lecture Notes in Computer Science
Event 23rd International Conference on Computational Science, ICCS 2023
Volume | Issue number I
Pages (from-to) 3-17
Publisher Cham: Springer
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract
The emergence of blockchain technologies has created the possibility of transforming business processes in the form of immutable agreements called smart contracts. Smart contracts suffer from a major limitation; they cannot authenticate the trustworthiness of real-world data sources, creating the need for intermediaries called oracles. Oracles are trusted entities that connect on-chain systems with off-chain data, allowing smart contracts to operate on real-world inputs in a trustworthy manner. A popular oracle protocol is a crowdsourced oracle, where unrelated individuals attest to facts through voting mechanisms in smart contracts. Crowdsourced oracles have unique challenges: the trustworthiness and correctness of outcomes cannot be explicitly verified. These problems are aggravated by inherent vulnerabilities to attacks, such as Sybil attacks. To address this weakness, this paper proposes a reputation-based mechanism, where oracles are given a reputation value depending on the implied correctness of their actions over time. This reputation score is used to eliminate malicious agents from the participant pool. Additionally, two reputation-based voting mechanisms are proposed. The effectiveness of the proposed mechanism is evaluated using an agent-based simulation of a crowdsourced oracle platform, where a pool of oracles performs evaluate Boolean queries.
Document type Conference contribution
Language English
Published at https://doi.org/10.1007/978-3-031-35995-8_1
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