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Evaluating Privacy Leakage in Split Learning

22 May 2023

Alex Sablayrolles

Papers citing "Evaluating Privacy Leakage in Split Learning"

31 / 31 papers shown

Title
ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity Xinchi Qiu Javier Fernandez-Marques Pedro Gusmão Yan Gao Titouan Parcollet Nicholas D. Lane FedML 69 71 0 04 Aug 2022
FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning Meisam Hejazinia Dzmitry Huba Ilias Leontiadis Kiwan Maeng Mani Malek Luca Melis Ilya Mironov Milad Nasr Kaikai Wang Carole-Jean Wu FedML 55 5 0 07 Jun 2022
Membership Inference Attacks From First Principles Nicholas Carlini Steve Chien Milad Nasr Shuang Song Andreas Terzis Florian Tramèr MIACV MIALM 83 704 0 07 Dec 2021
On the Importance of Difficulty Calibration in Membership Inference Attacks Lauren Watson Chuan Guo Graham Cormode Alex Sablayrolles 90 131 0 15 Nov 2021
See through Gradients: Image Batch Recovery via GradInversion Hongxu Yin Arun Mallya Arash Vahdat J. Álvarez Jan Kautz Pavlo Molchanov FedML 86 473 0 15 Apr 2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout Samuel Horváth Stefanos Laskaridis Mario Almeida Ilias Leondiadis Stylianos I. Venieris Nicholas D. Lane 219 274 0 26 Feb 2021
Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications Matthias Paulik M. Seigel Henry Mason Dominic Telaar Joris Kluivers ... Dominic Hughes O. Javidbakht Fei Dong Rehan Rishi Stanley Hung FedML 249 127 0 16 Feb 2021
Deep Learning with Label Differential Privacy Badih Ghazi Noah Golowich Ravi Kumar Pasin Manurangsi Chiyuan Zhang 100 151 0 11 Feb 2021
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown Basel Alomair Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 489 1,923 0 14 Dec 2020
Unleashing the Tiger: Inference Attacks on Split Learning Dario Pasquini G. Ateniese M. Bernaschi FedML 85 150 0 04 Dec 2020
SAPAG: A Self-Adaptive Privacy Attack From Gradients Yijue Wang Jieren Deng Danyi Guo Chenghong Wang Xianrui Meng Hang Liu Caiwen Ding Sanguthevar Rajasekaran 34 35 0 14 Sep 2020
Splintering with distributions: A stochastic decoy scheme for private computation Praneeth Vepakomma Julia Balla Ramesh Raskar FedML 107 2 0 06 Jul 2020
Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks Lixin Fan Kam Woh Ng Ce Ju Tianyu Zhang Chang Liu Chee Seng Chan Qiang Yang MIACV 33 64 0 20 Jun 2020
SplitFed: When Federated Learning Meets Split Learning Chandra Thapa Pathum Chamikara Mahawaga Arachchige S. Çamtepe Lichao Sun FedML 90 581 0 25 Apr 2020
The Future of Digital Health with Federated Learning Nicola Rieke Jonny Hancox Wenqi Li Fausto Milletari H. Roth ... Ronald M. Summers Andrew Trask Daguang Xu Maximilian Baust M. Jorge Cardoso OOD 259 1,774 0 18 Mar 2020
FedVision: An Online Visual Object Detection Platform Powered by Federated Learning Yang Liu Anbu Huang Yu Luo He Huang Youzhi Liu Yuanyuan Chen Lican Feng Tianjian Chen Hang Yu Qiang Yang FedML 155 301 0 17 Jan 2020
iDLG: Improved Deep Leakage from Gradients Bo Zhao Konda Reddy Mopuri Hakan Bilen FedML 66 637 0 08 Jan 2020
Bayesian Hyperparameter Optimization with BoTorch, GPyTorch and Ax Daniel T. Chang BDL AI4CE 21 11 0 11 Dec 2019
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 256 6,261 0 10 Dec 2019
Federated Learning for Ranking Browser History Suggestions Florian Hartmann Sunah Suh Arkadiusz Komarzewski Tim Smith I. Segall FedML 51 55 0 26 Nov 2019
White-box vs Black-box: Bayes Optimal Strategies for Membership Inference Alexandre Sablayrolles Matthijs Douze Yann Ollivier Cordelia Schmid Hervé Jégou MIACV 67 366 0 29 Aug 2019
Deep Leakage from Gradients Ligeng Zhu Zhijian Liu Song Han FedML 97 2,207 0 21 Jun 2019
Differentially Private Learning with Adaptive Clipping Galen Andrew Om Thakkar H. B. McMahan Swaroop Ramaswamy FedML 82 339 0 09 May 2019
Federated Optimization in Heterogeneous Networks Tian Li Anit Kumar Sahu Manzil Zaheer Maziar Sanjabi Ameet Talwalkar Virginia Smith FedML 180 5,184 0 14 Dec 2018
Distributed learning of deep neural network over multiple agents O. Gupta Ramesh Raskar FedML OOD 66 605 0 14 Oct 2018
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models A. Salem Yang Zhang Mathias Humbert Pascal Berrang Mario Fritz Michael Backes MIACV MIALM 94 949 0 04 Jun 2018
The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks Nicholas Carlini Chang-rui Liu Ulfar Erlingsson Jernej Kos Basel Alomair 144 1,143 0 22 Feb 2018
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction Huifeng Guo Ruiming Tang Yunming Ye Zhenguo Li Xiuqiang He 120 2,650 0 13 Mar 2017
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 261 4,135 0 18 Oct 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 216 6,130 0 01 Jul 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 406 17,486 0 17 Feb 2016