Preprint
Aug 2026
Efficient Privacy-Preserving Range Filtered Approximate Nearest Neighbor Search
This is the first study that systematically formulates and evaluates privacy-preserving RFANNS over outsourced encrypted vector databases, and improves the QPS-Recall trade-off over representative secure adaptations of existing RFANNS approaches, scaling effectively to large datasets.
Haoyu Wang, Yandi Zhang, Jia-Dong Xie et al.
· 0 citations