Privacy-preserving multi-party data joint analysis scheme based on multiset operations in smart contracts
Abstract With the advancement of blockchain technology, smart contracts are increasingly applied in finance, supply chain, healthcare, and other domains. However, the demand for multi-party data joint analysis within these contracts faces challenges of privacy leakage and malicious deception. This p...
Saved in:
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-07-01
|
| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44443-025-00107-1 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Abstract With the advancement of blockchain technology, smart contracts are increasingly applied in finance, supply chain, healthcare, and other domains. However, the demand for multi-party data joint analysis within these contracts faces challenges of privacy leakage and malicious deception. This paper applies secure multi-party computation (MPC) to smart contracts, based on the secure computation of intersection, union, and difference of multi-party multisets (IUDMM), to protect data privacy while supporting joint analysis. Existing multiset computation protocols are primarily designed for two-party scenarios under the semi-honest model, which are unsuitable for applications involving multiple participants in smart contracts. This paper introduces a protocol for IUDMM under the semi-honest model, utilizing the multi-key NTRU encryption algorithm and a novel vector encoding method. Furthermore, to address potential malicious behaviors, an IUDMM protocol under the malicious model is designed by incorporating digital commitment method. The protocol’s correctness is analyzed, and its security is proven using the real/ideal model paradigm. Additionally, it also resists collusion attacks by any party. Finally, efficiency analysis and experimental simulations demonstrate that the proposed protocols are efficient, reliable, and fair, providing a secure and practical solution for multi-party data joint analysis and privacy protection in smart contracts. |
|---|---|
| ISSN: | 1319-1578 2213-1248 |