Abstract
The increasing concerns on data security limit the sharing of data distributedly stored at multiple data owners and impede the scale of spatial queries over big urban data. In response, data federation systems have emerged to perform secure queries across multiple data owners leveraging secure multi-party computation. However, existing systems are designed for relational data. They are highly inefficient on spatial queries and limited in usability. In this demonstration, we introduce Hu-Fu, the first data federation system for secure spatial queries with high efficiency and usability. Hu-Fu is designed from the perspectives of the query user and the data owner for high usability and decomposes a spatial query into as many plaintext operators and as few secure operators as possible for high efficiency. We demonstrate the deployment and usage of Hu-Fu via cross-company taxi-calling, a popular smart city application. © 2022, VLDB Endowment. All rights reserved.
| Original language | English |
|---|---|
| Pages (from-to) | 3582-3585 |
| Journal | Proceedings of the VLDB Endowment |
| Volume | 15 |
| Issue number | 12 |
| Online published | 1 Aug 2022 |
| DOIs | |
| Publication status | Published - Aug 2022 |
| Externally published | Yes |
| Event | 48th International Conference on Very Large Data Bases (VLDB 2022) - The International Convention Centre Sydney (in-person & Online), Sydney, Australia Duration: 5 Sept 2022 → 9 Sept 2022 https://vldb.org/2022/ |
