SoK: Privacy-Preserving Collaborative Tree-based Model Learning

16 March 2021

Sylvain Chatel

Apostolos Pyrgelis

J. Troncoso-Pastoriza

Jean-Pierre Hubaux

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Papers citing "SoK: Privacy-Preserving Collaborative Tree-based Model Learning"

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Title
GTree: GPU-Friendly Privacy-preserving Decision Tree Training and Inference Qifan Wang Shujie Cui Lei Zhou Ye Dong Jianli Bai Yun Sing Koh Giovanni Russello 62 0 0 01 May 2023
Scalable and Provably Accurate Algorithms for Differentially Private Distributed Decision Tree Learning Kai Wang Travis Dick Maria-Florina Balcan FedML 27 5 0 19 Dec 2020
Secure Collaborative Training and Inference for XGBoost Andrew Law Chester Leung Rishabh Poddar Raluca A. Popa Chenyu Shi Octavian Sima Chaofan Yu Xingmeng Zhang Wenting Zheng FedML 39 33 0 06 Oct 2020
Privacy Preserving Vertical Federated Learning for Tree-based Models Yuncheng Wu Shaofeng Cai Xiaokui Xiao Gang Chen Beng Chin Ooi FedML 31 212 0 14 Aug 2020
Balance is key: Private median splits yield high-utility random trees Shorya Consul Sinead Williamson 42 2 0 15 Jun 2020
Cloud-based Federated Boosting for Mobile Crowdsensing Zhuzhu Wang Yilong Yang Yang Liu Ximeng Liu B. Gupta Jianfeng Ma FedML 31 13 0 09 May 2020
When Machine Unlearning Jeopardizes Privacy Min Chen Zhikun Zhang Tianhao Wang Michael Backes Mathias Humbert Yang Zhang MIACV 68 226 0 05 May 2020
Federated Extra-Trees with Privacy Preserving Yang Liu Mingxi Chen Wenxi Zhang Junbo Zhang Yu Zheng FedML 112 3 0 18 Feb 2020
Privacy-Preserving Boosting in the Local Setting Sen Wang J.Morris Chang FedML 38 3 0 06 Feb 2020
Boosted and Differentially Private Ensembles of Decision Trees Richard Nock Wilko Henecka 40 2 0 26 Jan 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 171 6,229 0 10 Dec 2019
SecureGBM: Secure Multi-Party Gradient Boosting Zhi Feng Haoyi Xiong Chuanyuan Song Sijia Yang Baoxin Zhao Licheng Wang Zeyu Chen Shengwen Yang Liping Liu Jun Huan FedML 32 52 0 27 Nov 2019
Privacy-Preserving Gradient Boosting Decision Trees Yue Liu Zhaomin Wu Zeyi Wen Bingsheng He 66 78 0 11 Nov 2019
Practical Federated Gradient Boosting Decision Trees Yue Liu Zeyi Wen Bingsheng He FedML AI4CE 100 191 0 11 Nov 2019
Revocable Federated Learning: A Benchmark of Federated Forest Yang Liu Zhuo Ma Ximeng Liu Zhuzhu Wang Siqi Ma Ken Ren FedML MU 37 10 0 08 Nov 2019
Boosting Privately: Privacy-Preserving Federated Extreme Boosting for Mobile Crowdsensing Yang Liu Zhuo Ma Ximeng Liu Siqi Ma Surya Nepal R. Deng FedML 53 63 0 24 Jul 2019
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection Yue Liu Zeyi Wen Zhaomin Wu Sixu Hu Naibo Wang Yuan N. Li Xu Liu Bingsheng He FedML 89 996 0 23 Jul 2019
The Tradeoff Between Privacy and Accuracy in Anomaly Detection Using Federated XGBoost Mengwei Yang Linqi Song Jie Xu Congduan Li Guozhen Tan FedML 97 31 0 16 Jul 2019
Deep Leakage from Gradients Ligeng Zhu Zhijian Liu Song Han FedML 78 2,199 0 21 Jun 2019
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks Maksym Andriushchenko Matthias Hein 62 61 0 08 Jun 2019
Federated Forest Yang Liu Yingting Liu Zhijie Liu Junbo Zhang Chuishi Meng Yu Zheng FedML 60 145 0 24 May 2019
Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning A. Salem Apratim Bhattacharyya Michael Backes Mario Fritz Yang Zhang FedML AAML MIACV 60 254 0 01 Apr 2019
SecureBoost: A Lossless Federated Learning Framework Kewei Cheng Tao Fan Yilun Jin Yang Liu Tianjian Chen Dimitrios Papadopoulos Qiang Yang FedML 93 583 0 25 Jan 2019
A Hybrid Approach to Privacy-Preserving Federated Learning Stacey Truex Nathalie Baracaldo Ali Anwar Thomas Steinke Heiko Ludwig Rui Zhang Yi Zhou FedML 52 891 0 07 Dec 2018
Privacy-Preserving Collaborative Prediction using Random Forests Irene Giacomelli S. Jha Ross Kleiman David Page Kyonghwan Yoon 66 24 0 21 Nov 2018
How To Backdoor Federated Learning Eugene Bagdasaryan Andreas Veit Yiqing Hua D. Estrin Vitaly Shmatikov SILM FedML 88 1,907 0 02 Jul 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 134 1,471 0 10 May 2018
Leaky Cauldron on the Dark Land: Understanding Memory Side-Channel Hazards in SGX Wenhao Wang Guoxing Chen Xiaorui Pan Yinqian Zhang Xiaofeng Wang Vincent Bindschaedler Haixu Tang Carl A. Gunter AAML 49 371 0 20 May 2017
What Does The Crowd Say About You? Evaluating Aggregation-based Location Privacy Apostolos Pyrgelis Carmela Troncoso Emiliano De Cristofaro 50 57 0 01 Mar 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 366 3,776 0 28 Feb 2017
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning Briland Hitaj G. Ateniese Fernando Perez-Cruz FedML 109 1,399 0 24 Feb 2017
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 226 4,103 0 18 Oct 2016
Predicting the future relevance of research institutions - The winning solution of the KDD Cup 2016 Vlad Sandulescu Mihail Chiru 29 51 0 09 Sep 2016
Differentially Private Random Decision Forests using Smooth Sensitivity Sam Fletcher M. Islam 36 82 0 11 Jun 2016
XGBoost: A Scalable Tree Boosting System Tianqi Chen Carlos Guestrin 556 38,735 0 09 Mar 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 301 17,399 0 17 Feb 2016
Encrypted statistical machine learning: new privacy preserving methods L. Aslett P. Esperança Chris C. Holmes 31 65 0 27 Aug 2015
Differentially- and non-differentially-private random decision trees Mariusz Bojarski A. Choromańska K. Choromanski Yann LeCun 65 31 0 26 Oct 2014
Hacking Smart Machines with Smarter Ones: How to Extract Meaningful Data from Machine Learning Classifiers G. Ateniese G. Felici L. Mancini A. Spognardi Antonio Villani Domenico Vitali 69 459 0 19 Jun 2013
A Noise Addition Scheme in Decision Tree for Privacy Preserving Data Mining M. A. Kadampur D. Somayajulu 104 39 0 20 Jan 2010
Privacy Preserving ID3 over Horizontally, Vertically and Grid Partitioned Data B. Kuijpers Vanessa Lemmens Bart Moelans K. Tuyls 83 16 0 11 Mar 2008