Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning System

Summary: Falcon is a privacy-preserving VFL system that combines threshold partially homomorphic encryption and additive secret sharing to enable secure training/prediction for linear, logistic, and MLP models with no intermediate leakage. Adds a decentralized, privacy-preserving interpretability framework and optimized data-parallel execution; implemented, matches plaintext accuracy and outperforms secure baselines in efficiency. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 13096
Venue: VLDB
Year: 2023
Pagerank: 5.031352e-05
Overall Rank: 6,498 | 54.84%
DOI: 10.14778/3603581.3603588

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
8,453	Secure and Verifiable Data Collaboration with Low-Cost Zero-Knowledge Proofs	2024	VLDB	4.5022073e-05
10,554	OpenFGL: A Comprehensive Benchmark for Federated Graph Learning	2025	VLDB	4.1905499e-05
10,672	Calibrating Noise for Group Privacy in Subsampled Mechanisms	2025	VLDB	4.1905499e-05
10,692	Federated Incomplete Tabular Data Prediction with Missing Complementarity	2025	VLDB	4.1905499e-05
10,694	PS-MI: Accurate, Efficient, and Private Data Valuation in Vertical Federated Learning	2025	VLDB	4.1905499e-05

Outgoing Citations (Sorted by Pagerank)

Showing 12 of 12 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
1,099	Privacy Preserving Vertical Federated Learning for Tree-based Models	2020	VLDB	0.00014063542
1,899	VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning	2021	SIGMOD	0.00010171063
2,791	CryptEpsilon: Crypto-Assisted Differential Privacy on Untrusted Servers	2020	SIGMOD	8.1198086e-05
3,475	BlindFL: Vertical Federated Machine Learning without Peeking into Your Data	2022	SIGMOD	7.0590045e-05
4,806	Projected Federated Averaging with Heterogeneous Differential Privacy	2022	VLDB	5.9045984e-05
5,227	Enabling SQL-based Training Data Debugging for Federated Learning	2022	VLDB	5.6156523e-05
5,784	Federated Matrix Factorization with Privacy Guarantee	2022	VLDB	5.3259797e-05
5,959	Fine-grained Concept Linking using Neural Networks in Healthcare	2018	SIGMOD	5.2514585e-05
7,401	Frequency Estimation Under Multiparty Differential Privacy: One-shot and Streaming	2022	VLDB	4.7351747e-05
9,328	FEAST: A Communication-efficient Federated Feature Selection Framework for Relational Data	2023	SIGMOD	4.351469e-05
11,189	Regularized Pairwise Relationship based Analytics for Structured Data	2023	SIGMOD	4.1905499e-05
11,598	TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications	2020	SIGMOD	4.1905499e-05

Semantically Similar Papers

Overall Rank	Paper	Year	Venue	Pagerank
5,784	Federated Matrix Factorization with Privacy Guarantee	2022	VLDB	5.3259797e-05
8,453	Secure and Verifiable Data Collaboration with Low-Cost Zero-Knowledge Proofs	2024	VLDB	4.5022073e-05
6,615	Differentially Private Vertical Federated Clustering	2023	VLDB	4.9882647e-05
9,373	Falcon: Fair Active Learning using Multi-armed Bandits	2024	VLDB	4.3460825e-05
1,899	VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning	2021	SIGMOD	0.00010171063
4,806	Projected Federated Averaging with Heterogeneous Differential Privacy	2022	VLDB	5.9045984e-05
11,046	Uldp-FL: Federated Learning with Across-Silo User-Level Differential Privacy	2024	VLDB	4.1905499e-05
3,504	FalconDB: Blockchain-based Collaborative Database	2020	SIGMOD	7.0305687e-05
1,099	Privacy Preserving Vertical Federated Learning for Tree-based Models	2020	VLDB	0.00014063542
3,475	BlindFL: Vertical Federated Machine Learning without Peeking into Your Data	2022	SIGMOD	7.0590045e-05