Traditional Insurance, a popular approach of financial risk management, has suffered from the issues of high operational costs, opaqueness, inefficiency and a lack of trust. Recently, blockchain-enabled "parametric insurance" through authorized data sources (e.g., remote sensing and IoT) aims to overcome these issues by automating the underwriting and claim processes of insurance policies on a blockchain. However, the openness of blockchain platforms raises a concern of user privacy, as the private user data in insurance claims on a blockchain may be exposed to outsiders. In this paper, we propose a privacy-preserving parametric insurance framework based on succinct zero-knowledge proofs (zk-SNARKs), whereby an insuree submits a zero-knowledge proof (without revealing any private data) for the validity of an insurance claim and the authenticity of its data sources to a blockchain for transparent verification. Moreover, we extend the recent zk-SNARKs to support robust privacy protection for multiple heterogeneous data sources and improve its efficiency to cut the incurred gas cost by 80%. As a proof-of-concept, we implemented a working prototype of bushfire parametric insurance on real-world blockchain platform Ethereum, and present extensive empirical evaluations.

翻译：传统保险作为金融风险管理的常用手段，长期面临运营成本高、透明度低、效率低下及信任缺失等问题。近年来，通过授权数据源（如遥感与物联网）驱动的"参数化保险"借助区块链技术，旨在通过将保单承保与索赔流程自动化来解决上述问题。然而，区块链平台的开放性引发了用户隐私担忧——区块链上保险索赔涉及的私有用户数据可能被外界获取。本文提出基于简洁零知识证明（zk-SNARKs）的隐私保护参数化保险框架，投保人可向区块链提交零知识证明（不泄露任何私有数据），验证保险索赔的有效性及其数据源的真实性，从而实现透明化验证。此外，我们扩展了现有zk-SNARKs技术，以支持多异构数据源的鲁棒隐私保护，并通过效率优化将产生的燃料成本降低80%。作为概念验证，我们在真实区块链平台Ethereum上实现了山火参数化保险的工作原型，并开展了全面的实证评估。