Database Paper Browser

Back to papers

Privacy Preserving Vertical Federated Learning for Tree-based Models

Summary: Pivot: privacy-preserving vertical FL for tree models with disjoint feature owners and one label holder, no TTP, secure against semi-honest m-1. Also mitigates plaintext leakage; extends to RF/GBDT by composing trees; results show efficiency. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12102
Venue
VLDB
Year
2020
Pagerank
0.00014063542
Overall Rank
1,099 | 92.37%
DOI
10.14778/3407790.3407811

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 19 of 19 citing papers.

Rank Citing Paper Year Venue Pagerank
1,899 VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning 2021 SIGMOD 0.00010171063
3,475 BlindFL: Vertical Federated Machine Learning without Peeking into Your Data 2022 SIGMOD 7.0590045e-05
4,282 FedTSC: A Secure Federated Learning System for Interpretable Time Series Classification 2022 VLDB 6.2824978e-05
5,227 Enabling SQL-based Training Data Debugging for Federated Learning 2022 VLDB 5.6156523e-05
5,521 OpBoost: A Vertical Federated Tree Boosting Framework Based on Order-Preserving Desensitization 2023 VLDB 5.4671745e-05
5,784 Federated Matrix Factorization with Privacy Guarantee 2022 VLDB 5.3259797e-05
6,498 Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning System 2023 VLDB 5.031352e-05
6,615 Differentially Private Vertical Federated Clustering 2023 VLDB 4.9882647e-05
7,487 Incentive-Aware Decentralized Data Collaboration 2023 SIGMOD 4.7135369e-05
7,702 ExDRa: Exploratory Data Science on Federated Raw Data 2021 SIGMOD 4.6689015e-05
8,453 Secure and Verifiable Data Collaboration with Low-Cost Zero-Knowledge Proofs 2024 VLDB 4.5022073e-05
9,328 FEAST: A Communication-efficient Federated Feature Selection Framework for Relational Data 2023 SIGMOD 4.351469e-05
9,965 Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updates 2022 VLDB 4.2229209e-05
10,101 Privacy-preserving and Verifiable Causal Prescriptive Analytics 2026 SIGMOD 4.1905499e-05
10,231 Bifrost: A Much Simpler Secure Two-Party Data Join Protocol for Secure Data Analytics 2026 VLDB 4.1905499e-05
10,402 SecureXGB: A Secure and Efficient Multi-party Protocol for Vertical Federated XGBoost 2025 SIGMOD 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
11,006 Performance-Based Pricing for Federated Learning via Auction 2024 VLDB 4.1905499e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

Rank Cited Paper Year Venue Pagerank
40 Privacy-Preserving Data Mining 2000 SIGMOD 0.00074213516
178 Boosting the Accuracy of Differentially Private Histograms Through Consistency 2010 VLDB 0.00037726596
2,791 CryptEpsilon: Crypto-Assisted Differential Privacy on Untrusted Servers 2020 SIGMOD 8.1198086e-05
2,858 TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial 2019 VLDB 8.0063362e-05
4,924 An Experimental Evaluation of Large Scale GBDT Systems 2019 VLDB 5.8211961e-05
Previous Page 1 / 1 Next

Semantically Similar Papers

Overall Rank Paper Year Venue Pagerank
10,402 SecureXGB: A Secure and Efficient Multi-party Protocol for Vertical Federated XGBoost 2025 SIGMOD 4.1905499e-05
6,498 Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning System 2023 VLDB 5.031352e-05
7,489 DeltaBoost: Gradient Boosting Decision Trees with Efficient Machine Unlearning 2023 SIGMOD 4.7135369e-05
4,806 Projected Federated Averaging with Heterogeneous Differential Privacy 2022 VLDB 5.9045984e-05
11,240 Olive: Oblivious Federated Learning on Trusted Execution Environment Against the Risk of Sparsification 2023 VLDB 4.1905499e-05
5,784 Federated Matrix Factorization with Privacy Guarantee 2022 VLDB 5.3259797e-05
6,615 Differentially Private Vertical Federated Clustering 2023 VLDB 4.9882647e-05
3,475 BlindFL: Vertical Federated Machine Learning without Peeking into Your Data 2022 SIGMOD 7.0590045e-05
5,521 OpBoost: A Vertical Federated Tree Boosting Framework Based on Order-Preserving Desensitization 2023 VLDB 5.4671745e-05
1,899 VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning 2021 SIGMOD 0.00010171063