Blockchain-based multi-institution collaborative credit evaluation modeling method

Abstract

Multi-institution credit data sharing-aggregation can improve the accuracy of credit evaluation, however, it also encounters the problems of data fraud, and the privacy, compliance of collaborative modeling. Faced with increasingly stringent and comprehensive privacy protection regulations, the potential security risk call into question the current data sharing-aggregation mode. Blockchain has shown that trusted and auditable computing is possible using a decentralized network of peers, and the immutable distributed ledger. Moreover, oblivious transfer (OT) guarantees the confidentiality of cross-institution transmission and calculation. The integration of blockchain with OT is rapidly increasing in computing environment. In this paper, we design and implement a blockchain-OT-based credit evaluation system dubbed as MEChain. Blockchain acts as a distributed ledger which facilitates efficient and credible data sharing-aggregation. Combined the 1-out-of-N OT, data transformation is used for raw data encryption achieving private, secure, and compliant sharing-aggregation operations. The calculation case and security analysis, prototype system implementation, performance and accuracy rate analysis are presented to validate the proposed solution.