Infochain: A Decentralized, Trustless and Transparent Oracle on Blockchain

Infochain: A Decentralized, Trustless and Transparent Oracle on Blockchain

Naman Goel, Cyril van Schreven, Aris Filos-Ratsikas, Boi Faltings

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Special Track on AI in FinTech. Pages 4604-4610. https://doi.org/10.24963/ijcai.2020/635

Blockchain based systems allow various kinds of financial transactions to be executed in a decentralized manner. However, these systems often rely on a trusted third party (oracle) to get correct information about the real-world events, which trigger the financial transactions. In this paper, we identify two biggest challenges in building decentralized, trustless and transparent oracles. The first challenge is acquiring correct information about the real-world events without relying on a trusted information provider. We show how a peer-consistency incentive mechanism can be used to acquire truthful information from an untrusted and self-interested crowd, even when the crowd has outside incentives to provide wrong informations. The second is a system design and implementation challenge. For the first time, we show how to implement a trustless and transparent oracle in Ethereum. We discuss various non-trivial issues that arise in implementing peer-consistency mechanisms in Ethereum, suggest several optimizations to reduce gas cost and provide empirical analysis.
Keywords:
Foundation for AI in FinTech: AI for financial infrastructure
Foundation for AI in FinTech: Modeling economic incentives
Foundation for AI in FinTech: Modeling economic mechanisms and social welfare
AI for lending: AI for blockchain
AI for lending: AI for smart contracts
Foundation for AI in FinTech: General