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

Summary: Falcon combines threshold partially homomorphic encryption and additive secret sharing for private VFL training and inference across linear, logistic, and MLP models. It uniquely adds decentralized, privacy-preserving interpretability and optimized data parallelism. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: 13283
Venue: VLDB
Year: 2023
Pagerank: 5.8819368e-05
Overall Rank: 6,421 | 55.95%
DOI: 10.14778/3603581.3603588

Incoming Non-self Citations Over Time

Authors

1. Yuncheng Wu (National University of Singapore)
2. Naili Xing (National University of Singapore)
3. Gang Chen (Zhejiang University)
4. Tien Tuan Anh Dinh (Deakin University)
5. Zhaojing Luo (National University of Singapore)
6. Beng Chin Ooi (National University of Singapore)
7. Xiaokui Xiao (National University of Singapore)
8. Meihui Zhang (Beijing Institute of Technology)

BibTeX Citation

@article{wu_vldb23,
        title = {{Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning System}},
        author = {Wu, Yuncheng and Xing, Naili and Chen, Gang and Dinh, Tien Tuan Anh and Luo, Zhaojing and Ooi, Beng Chin and Xiao, Xiaokui and Zhang, Meihui},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {10},
        pages = {2471--2484},
        doi = {10.14778/3603581.3603588},
        url = {https://doi.org/10.14778/3603581.3603588},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
8,456	Secure and Verifiable Data Collaboration with Low-Cost Zero-Knowledge Proofs	2024	VLDB	5.4217837e-05
10,214	CoShap: A Scalable Coalition Growth Approach to Shapley Value Approximation	2026	SIGMOD	5.093636e-05
10,817	OpenFGL: A Comprehensive Benchmark for Federated Graph Learning	2025	VLDB	5.093636e-05
10,914	Calibrating Noise for Group Privacy in Subsampled Mechanisms	2025	VLDB	5.093636e-05
10,932	Federated Incomplete Tabular Data Prediction with Missing Complementarity	2025	VLDB	5.093636e-05
10,934	PS-MI: Accurate, Efficient, and Private Data Valuation in Vertical Federated Learning	2025	VLDB	5.093636e-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
1,249	Privacy Preserving Vertical Federated Learning for Tree-based Models	2020	VLDB	0.00011495357
1,959	VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning	2021	SIGMOD	9.4090198e-05
2,818	CryptEpsilon: Crypto-Assisted Differential Privacy on Untrusted Servers	2020	SIGMOD	8.0932359e-05
3,237	BlindFL: Vertical Federated Machine Learning without Peeking into Your Data	2022	SIGMOD	7.6089416e-05
4,446	Projected Federated Averaging with Heterogeneous Differential Privacy	2022	VLDB	6.6990707e-05
5,131	Enabling SQL-based Training Data Debugging for Federated Learning	2022	VLDB	6.3537809e-05
5,588	Federated Matrix Factorization with Privacy Guarantee	2022	VLDB	6.1564686e-05
6,115	Fine-grained Concept Linking using Neural Networks in Healthcare	2018	SIGMOD	5.9709282e-05
7,488	Frequency Estimation Under Multiparty Differential Privacy: One-shot and Streaming	2022	VLDB	5.6072422e-05
9,473	FEAST: A Communication-efficient Federated Feature Selection Framework for Relational Data	2023	SIGMOD	5.2634238e-05
11,391	Regularized Pairwise Relationship based Analytics for Structured Data	2023	SIGMOD	5.093636e-05
11,789	TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications	2020	SIGMOD	5.093636e-05

Semantically Similar Papers

#	Overall Rank	Paper	Year	Venue
1	5,588	Federated Matrix Factorization with Privacy Guarantee	2022	VLDB
2	8,456	Secure and Verifiable Data Collaboration with Low-Cost Zero-Knowledge Proofs	2024	VLDB
3	6,353	Differentially Private Vertical Federated Clustering	2023	VLDB
4	8,043	Falcon: Fair Active Learning using Multi-armed Bandits	2024	VLDB
5	1,959	VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning	2021	SIGMOD
6	4,446	Projected Federated Averaging with Heterogeneous Differential Privacy	2022	VLDB
7	11,252	Uldp-FL: Federated Learning with Across-Silo User-Level Differential Privacy	2024	VLDB
8	3,122	FalconDB: Blockchain-based Collaborative Database	2020	SIGMOD
9	1,249	Privacy Preserving Vertical Federated Learning for Tree-based Models	2020	VLDB
10	3,237	BlindFL: Vertical Federated Machine Learning without Peeking into Your Data	2022	SIGMOD