Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning with SGX

4 May 2021

Papers citing "Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning with SGX"

36 / 36 papers shown

Title
PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments Fan Mo Hamed Haddadi Kleomenis Katevas Eduard Marin Diego Perino N. Kourtellis FedML 106 245 0 29 Apr 2021
secureTF: A Secure TensorFlow Framework D. Quoc Franz Gregor Sergei Arnautov Roland Kunkel Pramod Bhatotia Christof Fetzer 62 40 0 20 Jan 2021
PrivColl: Practical Privacy-Preserving Collaborative Machine Learning Yanjun Zhang Guangdong Bai Xue Li Caitlin I. Curtis Chong Chen R. Ko FedML 41 33 0 14 Jul 2020
On the Generalization Benefit of Noise in Stochastic Gradient Descent Samuel L. Smith Erich Elsen Soham De MLT 49 99 0 26 Jun 2020
PrivFL: Practical Privacy-preserving Federated Regressions on High-dimensional Data over Mobile Networks K. Mandal G. Gong FedML 124 72 0 05 Apr 2020
Trust Management as a Service: Enabling Trusted Execution in the Face of Byzantine Stakeholders Franz Gregor W. Ożga Sébastien Vaucher Rafael Pires D. Quoc Sergei Arnautov André Martin V. Schiavoni Pascal Felber Christof Fetzer 42 32 0 31 Mar 2020
Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning Jinhyun So Başak Güler A. Avestimehr FedML 79 298 0 11 Feb 2020
Occlum: Secure and Efficient Multitasking Inside a Single Enclave of Intel SGX Youren Shen H. Tian Yu Chen Kang Chen Runji Wang Yi Xu Yubin Xia 44 154 0 21 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 208 6,229 0 10 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 391 42,299 0 03 Dec 2019
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization Farzin Haddadpour Mohammad Mahdi Kamani M. Mahdavi V. Cadambe FedML 64 201 0 30 Oct 2019
Why gradient clipping accelerates training: A theoretical justification for adaptivity J.N. Zhang Tianxing He S. Sra Ali Jadbabaie 72 459 0 28 May 2019
TensorSCONE: A Secure TensorFlow Framework using Intel SGX Roland Kunkel D. Quoc Franz Gregor Sergei Arnautov Pramod Bhatotia Christof Fetzer FedML 34 67 0 12 Feb 2019
SecureBoost: A Lossless Federated Learning Framework Kewei Cheng Tao Fan Yilun Jin Yang Liu Tianjian Chen Dimitrios Papadopoulos Qiang Yang FedML 95 583 0 25 Jan 2019
A General Approach to Adding Differential Privacy to Iterative Training Procedures H. B. McMahan Galen Andrew Ulfar Erlingsson Steve Chien Ilya Mironov Nicolas Papernot Peter Kairouz 64 193 0 15 Dec 2018
Secure Federated Transfer Learning Yang Liu Yan Kang Chaoping Xing Tianjian Chen Qiang Yang FedML 44 119 0 08 Dec 2018
Knockoff Nets: Stealing Functionality of Black-Box Models Tribhuvanesh Orekondy Bernt Schiele Mario Fritz MLAU 86 534 0 06 Dec 2018
Split learning for health: Distributed deep learning without sharing raw patient data Praneeth Vepakomma O. Gupta Tristan Swedish Ramesh Raskar FedML 118 702 0 03 Dec 2018
Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD Jianyu Wang Gauri Joshi FedML 65 232 0 19 Oct 2018
Distributed learning of deep neural network over multiple agents O. Gupta Ramesh Raskar FedML OOD 54 603 0 14 Oct 2018
Don't Use Large Mini-Batches, Use Local SGD Tao R. Lin Sebastian U. Stich Kumar Kshitij Patel Martin Jaggi 111 433 0 22 Aug 2018
Efficient Deep Learning on Multi-Source Private Data Nicholas Hynes Raymond Cheng D. Song FedML 57 102 0 17 Jul 2018
How To Backdoor Federated Learning Eugene Bagdasaryan Andreas Veit Yiqing Hua D. Estrin Vitaly Shmatikov SILM FedML 94 1,907 0 02 Jul 2018
PipeDream: Fast and Efficient Pipeline Parallel DNN Training A. Harlap Deepak Narayanan Amar Phanishayee Vivek Seshadri Nikhil R. Devanur G. Ganger Phillip B. Gibbons AI4CE 54 253 0 08 Jun 2018
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware Florian Tramèr Dan Boneh FedML 168 396 0 08 Jun 2018
Chiron: Privacy-preserving Machine Learning as a Service T. Hunt Congzheng Song Reza Shokri Vitaly Shmatikov Emmett Witchel 41 201 0 15 Mar 2018
Differentially Private Federated Learning: A Client Level Perspective Robin C. Geyer T. Klein Moin Nabi FedML 114 1,293 0 20 Dec 2017
Sparse Communication for Distributed Gradient Descent Alham Fikri Aji Kenneth Heafield 66 740 0 17 Apr 2017
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning Briland Hitaj G. Ateniese Fernando Perez-Cruz FedML 111 1,399 0 24 Feb 2017
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 230 4,103 0 18 Oct 2016
An overview of gradient descent optimization algorithms Sebastian Ruder ODL 198 6,179 0 15 Sep 2016
Stealing Machine Learning Models via Prediction APIs Florian Tramèr Fan Zhang Ari Juels Michael K. Reiter Thomas Ristenpart SILM MLAU 102 1,803 0 09 Sep 2016
TensorFlow: A system for large-scale machine learning Martín Abadi P. Barham Jianmin Chen Zhiwen Chen Andy Davis ... Vijay Vasudevan Pete Warden Martin Wicke Yuan Yu Xiaoqiang Zhang GNN AI4CE 417 18,334 0 27 May 2016
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 66 3,676 0 08 Feb 2016
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization Xiangru Lian Yijun Huang Y. Li Ji Liu 135 499 0 27 Jun 2015
ADADELTA: An Adaptive Learning Rate Method Matthew D. Zeiler ODL 132 6,623 0 22 Dec 2012