FedKNN: Secure Federated k-Nearest Neighbor Search

Summary: FedKNN enables secure federated kNN with diverse similarity measures, tackling privacy-preserving computation for hard-to-compute distances (graph/sequence). It introduces DANN and DANN* (differentially oblivious) to minimize local work, offering privacy–efficiency trade-offs with up to 4.8x/2.7x gains on graph/sequence kNN. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6820
Venue: SIGMOD
Year: 2024
Pagerank: 7.7586458e-05
Overall Rank: 2,996 | 79.16%
DOI: 10.1145/3639266

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
7,072	FedSQ: A Secure System for Federated Vector Similarity Queries	2024	VLDB	4.842703e-05
10,545	OpenFGL: A Comprehensive Benchmark for Federated Graph Learning	2025	VLDB	4.1945683e-05
10,819	FedVSE: A Privacy-Preserving and Efficient Vector Search Engine for Federated Databases	2025	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 9 of 9 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
951	Comparing Stars: On Approximating Graph Edit Distance	2009	VLDB	0.00015106325
1,364	Improving Approximate Nearest Neighbor Search through Learned Adaptive Early Termination	2020	SIGMOD	0.00012370117
2,670	Efficient Oblivious Database Joins	2020	VLDB	8.3379158e-05
3,024	Secure Yannakakis: Join-Aggregate Queries over Private Data	2021	SIGMOD	7.692511e-05
3,159	Towards Practical Oblivious Join	2022	SIGMOD	7.4630494e-05
4,036	Adore: Differentially Oblivious Relational Database Operators	2023	VLDB	6.5089579e-05
5,746	Hu-Fu: Efficient and Secure Spatial Queries over Data Federation	2022	VLDB	5.3420687e-05
6,839	Boosting Graph Similarity Search through Pre-Computation	2021	SIGMOD	4.9109527e-05
6,976	Flare: A Fast, Secure, and Memory-Efficient Distributed Analytics Framework	2023	VLDB	4.876497e-05

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