A semi-homomorphic privacy computing solution based on SM2 and blockchain
Yutao Shi, Kangqian Cao, Jie Yao, Xin Ge · 2023
In recent years, China's digital industrialisation and digitisation of industries have continued to develop in depth, and online transactions have become the shopping choice of many internet users. The strong endogenous dynamics have put forward requirements for high efficiency, low cost, high security and high privacy for online mobile payments. Blockchain is a technology that has emerged with the popularity of digital cryptocurrencies such as Bitcoin, which is characterised by "decentralisation" and "immutability", but blockchain transactions have privacy protection flaws and problems that seriously threaten the privacy and security of transaction users. This paper proposes a clear solution to this problem by combining homomorphic encryption and ethereum's smart contract technology to design a blockchain online transaction privacy protection system that is compatible with heterogeneous trading platforms. This effectively makes up for the shortcomings of blockchain technology in terms of privacy protection. The security of this scheme has been proven to be unforgeable and the privacy data is safe. Through performance simulation experiments and theoretical derivation, it is proved that the privacy data is distributed, shared and computed in a ciphertext state in a more efficient way, and the proposed scheme can protect customer privacy more effectively than the traditional model.