Abstract
Secure collaborative analytics enables multiple data owners to contribute their data to perform query analytics without learning each other's data. Although current systems are well-optimized for horizontal scenarios, they are not as effective in vertical scenarios. The join operator is the key performance bottleneck of vertically collaborative data analysis. The existing secure nested-loop two-way join approach results in O(n2) computation and communication complexity, where n represents table size. In this paper, we propose HSSCOA, a secure collaborative analytics system to execute join-aggregation queries on secret-shared database. particularly, we propose a simplified homomorphic secret sharing (HSS) supporting just single multiplication, called one-time multiplication HSS. Combined with secret-shared sorting protocol, we then design a secure and efficient two-way join protocol that achieves constant rounds of interaction and O(n log n) communication. We further extend our framework to support multi-way joins and various join variants. Comprehensive experiments implemented on MP-SPDZ demonstrate that HSSCOA significantly outperforms existing sort-based protocols in WAN settings due to its constant-round design.
| Original language | English |
|---|---|
| Journal | IEEE Transactions on Services Computing |
| DOIs | |
| State | Accepted/In press - 2026 |
| Externally published | Yes |
Keywords
- Homomorphic Secret Sharing
- Secret-Shared Join
- Secure Collaborative Analysis
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