Privacy and Robustness in Federated Learning: Attacks and Defenses

7 December 2020

Lichao Sun

Jun Zhao

Qiang Yang

Philip S. Yu

FedML

ArXiv PDF HTML

Papers citing "Privacy and Robustness in Federated Learning: Attacks and Defenses"

30 / 130 papers shown

Title
Byzantine Stochastic Gradient Descent Dan Alistarh Zeyuan Allen-Zhu Jingkai Li FedML 68 296 0 23 Mar 2018
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett OOD FedML 118 1,500 0 05 Mar 2018
Generalized Byzantine-tolerant SGD Cong Xie Oluwasanmi Koyejo Indranil Gupta AAML 73 258 0 27 Feb 2018
Scalable Private Learning with PATE Nicolas Papernot Shuang Song Ilya Mironov A. Raghunathan Kunal Talwar Ulfar Erlingsson 100 616 0 24 Feb 2018
The Hidden Vulnerability of Distributed Learning in Byzantium El-Mahdi El-Mhamdi R. Guerraoui Sébastien Rouault AAML FedML 67 748 0 22 Feb 2018
Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications M. Riazi Christian Weinert Oleksandr Tkachenko Ebrahim M. Songhori T. Schneider F. Koushanfar FedML 46 494 0 10 Jan 2018
Differentially Private Federated Learning: A Client Level Perspective Robin C. Geyer T. Klein Moin Nabi FedML 125 1,295 0 20 Dec 2017
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning Xinyun Chen Chang-rui Liu Yue Liu Kimberly Lu D. Song AAML SILM 135 1,837 0 15 Dec 2017
Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption Stephen Hardy Wilko Henecka Hamish Ivey-Law Richard Nock Giorgio Patrini Guillaume Smith Brian Thorne FedML 65 535 0 29 Nov 2017
Neural Trojans Yuntao Liu Yang Xie Ankur Srivastava AAML 49 354 0 03 Oct 2017
Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization Luis Muñoz-González Battista Biggio Ambra Demontis Andrea Paudice Vasin Wongrassamee Emil C. Lupu Fabio Roli AAML 99 632 0 29 Aug 2017
BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain Tianyu Gu Brendan Dolan-Gavitt S. Garg SILM 120 1,772 0 22 Aug 2017
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 157 2,151 0 21 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 304 12,069 0 19 Jun 2017
Certified Defenses for Data Poisoning Attacks Jacob Steinhardt Pang Wei Koh Percy Liang AAML 92 755 0 09 Jun 2017
Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers Jacob Steinhardt Moses Charikar Gregory Valiant 64 140 0 15 Mar 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 208 2,894 0 14 Mar 2017
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning Briland Hitaj G. Ateniese Fernando Perez-Cruz FedML 117 1,404 0 24 Feb 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 339 4,626 0 10 Nov 2016
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 249 4,135 0 18 Oct 2016
Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data Nicolas Papernot Martín Abadi Ulfar Erlingsson Ian Goodfellow Kunal Talwar 77 1,017 0 18 Oct 2016
Stealing Machine Learning Models via Prediction APIs Florian Tramèr Fan Zhang Ari Juels Michael K. Reiter Thomas Ristenpart SILM MLAU 107 1,805 0 09 Sep 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 203 6,121 0 01 Jul 2016
On the Convergence of A Family of Robust Losses for Stochastic Gradient Descent Bo Han Ivor W. Tsang Ling-Hao Chen NoLa 67 21 0 05 May 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 17,468 0 17 Feb 2016
Learning Privately from Multiparty Data Jihun Hamm Yingjun Cao M. Belkin FedML 45 165 0 10 Feb 2016
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response Ulfar Erlingsson Vasyl Pihur Aleksandra Korolova 96 1,992 0 25 Jul 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 270 14,918 1 21 Dec 2013
Poisoning Attacks against Support Vector Machines Battista Biggio B. Nelson Pavel Laskov AAML 112 1,590 0 27 Jun 2012
Differentially Private Empirical Risk Minimization Kamalika Chaudhuri C. Monteleoni Anand D. Sarwate 128 1,487 0 01 Dec 2009