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: 6821
Venue: SIGMOD
Year: 2024
Pagerank: 7.0241303e-05
Overall Rank: 4,017 | 72.09%
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
6,729	FedSQ: A Secure System for Federated Vector Similarity Queries	2024	VLDB	5.847135e-05
10,554	OpenFGL: A Comprehensive Benchmark for Federated Graph Learning	2025	VLDB	5.1725247e-05
10,824	FedVSE: A Privacy-Preserving and Efficient Vector Search Engine for Federated Databases	2025	VLDB	5.1725247e-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
957	Improving Approximate Nearest Neighbor Search through Learned Adaptive Early Termination	2020	SIGMOD	0.00013044785
1,099	Comparing Stars: On Approximating Graph Edit Distance	2009	VLDB	0.00012271234
2,089	Efficient Oblivious Database Joins	2020	VLDB	9.256923e-05
2,608	Secure Yannakakis: Join-Aggregate Queries over Private Data	2021	SIGMOD	8.4205138e-05
2,663	Towards Practical Oblivious Join	2022	SIGMOD	8.3448927e-05
3,987	Adore: Differentially Oblivious Relational Database Operators	2023	VLDB	7.0447891e-05
5,648	Hu-Fu: Efficient and Secure Spatial Queries over Data Federation	2022	VLDB	6.2008767e-05
7,043	Boosting Graph Similarity Search through Pre-Computation	2021	SIGMOD	5.77042e-05
7,057	Flare: A Fast, Secure, and Memory-Efficient Distributed Analytics Framework	2023	VLDB	5.7676713e-05

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