A Secure and Large-Scale Multiparty Conditional Payment Scheme based on Blockchain

Although artificial intelligence can enhance the value of big data and blockchain, it poses serious threats to personal privacy data and enterprise business secrets, making the problem of data island one of the biggest obstacles and bottlenecks restricting the development of blockchain. Blockchain, as a public distributed ledger technology, have particularly been deployed in some mature payment systems with widespread adoption. While the ever-growing network congestion, transaction costs and continuously dropping transaction rates limit its large-scale and widespread applications. To address these issues, in this paper we first propose two new definitions about an aggregated signature with deterability and a conditional anonymous multiparty payment scheme. Then the security requirements of the conditional anonymous multiparty payment scheme are described and a concrete anonymous multiparty payment scheme is constructed based on an aggregated signatures with deterability (ASE for short) and a conditional anonymous multiparty payment scheme with punishability (CAPP for short), whose security can be demonstrated under the security model. Finally, we compare the security of our scheme with other related works and make some evaluations to show the utility of our scheme.