Double-Blind KYC Data Sharing Blockchain Framework
管理學院 - 資訊管理系
Department of Information Management
|Thesis Publication Year:||2021|
|Graduation Academic Year:||109|
|Keywords (in Chinese):||區塊鏈 、IPFS 、Know Your Customer(KYC) 、雙盲|
|Keywords (in other languages):||Blockchain, IPFS, Know Your Customer(KYC), Double-Blind|
|Reference times:||Clicks: 60 Downloads: 0|
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The first step in a financial institution's Know-Your-Customer (KYC) process is to collect and verify customer data and identify the customer. The traditional approach is not only time consuming but also costly. While several blockchain-based solutions can reuse customer data, most of them reveal the relationship between the financial institution and the customer during the process. This affects the willingness of participating in KYC data sharing platforms because, in the real world, financial institutions have a competitive business relationship with each other and do not want to be less competitive by revealing information.
This thesis proposes a double-blind KYC data sharing blockchain framework. The framework combines blockchain and IPFS technologies. It uses associations to run proxy nodes in consortium blockchains and execute blockchain transactions on behalf of multiple banks to mix the identity of banks on the blockchain. This allows the banks to share data without revealing their identities in the process and enables double-blind data sharing. The authorized sharing and requesting protocol utilize warrants to ensure that banks and associations can only perform data sharing with the customer's authorized consent. In addition, an auditor will conduct automated audits during the processes. Finally, we ran performance experiments of the authorized requesting protocol with different numbers of banks and performed security analysis on the framework. The results show that our framework helps banks to securely and efficiently get customer KYC data from other banks. In an experiment with 32 banks, the bank obtained 32 KYC files at an average speed of 1.63 seconds per 5MB file.
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