Research on privacy enhancement scheme of blockchain transactions

Tao Feng, Xuan Chen, Chunyan Liu, Xiaoqin Feng · Security and Privacy · 2019

Abstract Blockchain is the supporting technology for cryptocurrencies, which can be used to record transaction information among users. However, the information on blockchain can be accessed and verified by any user. To some extent, it is effortless to acquire users' identities, transaction privacy information by means of transaction tracing technology and data analysis technology. In order to tackle the above problems, we proposed a transaction privacy enhancement scheme based on the computational Diffie‐Hellman problem with provable security. By leveraging a group signature scheme, the mixing peer can mix the transactions so that the transaction sender can be hidden into a mixing group. In addition, our solution improves the efficiency by utilizing a signature aggregation scheme and reducing the overhead of the signature verification. The security analysis shows that the proposed scheme is superior in privacy and the efficiency of signature verification.

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