Title | A Truth-Inducing Sybil Resistant Decentralized Blockchain Oracle |
Publication Type | Conference Paper |
Year of Publication | 2020 |
Authors | Cai, Y., Fragkos, G., Tsiropoulou, E. E., Veneris, A. |
Conference Name | 2020 2nd Conference on Blockchain Research Applications for Innovative Networks and Services (BRAINS) |
Keywords | composability, cryptography, decentralized oracle protocols, Decentralized Oracles, Distributed databases, majority-voting schemes, maximized expected score, Metrics, nonlinear stake scaling rule, Peer Prediction, peer prediction scoring scheme, pubcrawl, Resiliency, Staked Voting, sybil attacks, truth-inducing Sybil resistant decentralized blockchain oracle |
Abstract | Many blockchain applications use decentralized oracles to trustlessly retrieve external information as those platforms are agnostic to real-world information. Some existing decentralized oracle protocols make use of majority-voting schemes to determine the outcomes and/or rewards to participants. In these cases, the awards (or penalties) grow linearly to the participant stakes, therefore voters are indifferent between voting through a single or multiple identities. Furthermore, the voters receive a reward only when they agree with the majority outcome, a tactic that may lead to herd behavior. This paper proposes an oracle protocol based on peer prediction mechanisms with non-linear staking rules. In the proposed approach, instead of being rewarded when agreeing with a majority outcome, a voter receives awards when their report achieves a relatively high score based on a peer prediction scoring scheme. The scoring scheme is designed to be incentive compatible so that the maximized expected score is achieved only with honest reporting. A non-linear stake scaling rule is proposed to discourage Sybil attacks. This paper also provides a theoretical analysis and guidelines for implementation as reference. |
DOI | 10.1109/BRAINS49436.2020.9223272 |
Citation Key | cai_truth-inducing_2020 |