Femur: A Flexible Framework for Fast and Secure Querying from Public Key-Value Store
Summary: Introduces distance-based indistinguishability to obtain provable privacy–performance trade-offs for public key-value querying. Femur combines a space-efficient learned index, noise-based obfuscation of storage ranges, and a variable-range PIR to adaptively maximize throughput (up to 163.9x) under relaxed privacy. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jiaoyi Zhang (Tsinghua University)
- 2. Liqiang Peng (Alibaba)
- 3. Mo Sha (Alibaba)
- 4. Weiran Liu (Alibaba)
- 5. Xiang Li (Tsinghua University)
- 6. Sheng Wang (Alibaba)
- 7. Feifei Li (Alibaba)
- 8. Mingyu Gao (Shanghai Qi Zhi Institute; Tsinghua University)
- 9. Huanchen Zhang (Shanghai Qi Zhi Institute; Tsinghua University)
BibTeX Citation
@inproceedings{zhang_sigmod25,
title = {{Femur: A Flexible Framework for Fast and Secure Querying from Public Key-Value Store}},
author = {Zhang, Jiaoyi and Peng, Liqiang and Sha, Mo and Liu, Weiran and Li, Xiang and Wang, Sheng and Li, Feifei and Gao, Mingyu and Zhang, Huanchen},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3725299},
url = {https://dl.acm.org/doi/10.1145/3725299},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,264 | Loom: Weaving PCS-Preserving and Searchable Cloud Backups for Secure Messaging | 2026 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 39 of 39 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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