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: 13095
Venue: VLDB
Year: 2023
Pagerank: 5.0361846e-05
Overall Rank: 6,502 | 54.77%
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
8,459	Secure and Verifiable Data Collaboration with Low-Cost Zero-Knowledge Proofs	2024	VLDB	4.5065275e-05
10,545	OpenFGL: A Comprehensive Benchmark for Federated Graph Learning	2025	VLDB	4.1945683e-05
10,664	Calibrating Noise for Group Privacy in Subsampled Mechanisms	2025	VLDB	4.1945683e-05
10,684	Federated Incomplete Tabular Data Prediction with Missing Complementarity	2025	VLDB	4.1945683e-05
10,686	PS-MI: Accurate, Efficient, and Private Data Valuation in Vertical Federated Learning	2025	VLDB	4.1945683e-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
1,143	Privacy Preserving Vertical Federated Learning for Tree-based Models	2020	VLDB	0.00013710269
1,895	VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning	2021	SIGMOD	0.00010180896
2,806	CryptEpsilon: Crypto-Assisted Differential Privacy on Untrusted Servers	2020	SIGMOD	8.0911177e-05
3,506	BlindFL: Vertical Federated Machine Learning without Peeking into Your Data	2022	SIGMOD	7.0291192e-05
4,805	Projected Federated Averaging with Heterogeneous Differential Privacy	2022	VLDB	5.9102798e-05
5,222	Enabling SQL-based Training Data Debugging for Federated Learning	2022	VLDB	5.6210545e-05
5,775	Federated Matrix Factorization with Privacy Guarantee	2022	VLDB	5.3310992e-05
5,958	Fine-grained Concept Linking using Neural Networks in Healthcare	2018	SIGMOD	5.2563968e-05
7,401	Frequency Estimation Under Multiparty Differential Privacy: One-shot and Streaming	2022	VLDB	4.7397228e-05
9,323	FEAST: A Communication-efficient Federated Feature Selection Framework for Relational Data	2023	SIGMOD	4.3556432e-05
11,187	Regularized Pairwise Relationship based Analytics for Structured Data	2023	SIGMOD	4.1945683e-05
11,594	TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications	2020	SIGMOD	4.1945683e-05

Semantically Similar Papers

Overall Rank	Paper	Year	Venue	Pagerank
5,775	Federated Matrix Factorization with Privacy Guarantee	2022	VLDB	5.3310992e-05
8,459	Secure and Verifiable Data Collaboration with Low-Cost Zero-Knowledge Proofs	2024	VLDB	4.5065275e-05
6,700	Differentially Private Vertical Federated Clustering	2023	VLDB	4.9563668e-05
9,365	Falcon: Fair Active Learning using Multi-armed Bandits	2024	VLDB	4.3502315e-05
1,895	VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning	2021	SIGMOD	0.00010180896
4,805	Projected Federated Averaging with Heterogeneous Differential Privacy	2022	VLDB	5.9102798e-05
11,043	Uldp-FL: Federated Learning with Across-Silo User-Level Differential Privacy	2024	VLDB	4.1945683e-05
3,500	FalconDB: Blockchain-based Collaborative Database	2020	SIGMOD	7.0373486e-05
1,143	Privacy Preserving Vertical Federated Learning for Tree-based Models	2020	VLDB	0.00013710269
3,506	BlindFL: Vertical Federated Machine Learning without Peeking into Your Data	2022	SIGMOD	7.0291192e-05