The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation

12 February 2021

Papers citing "The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation"

50 / 141 papers shown

Title
Privacy-Preserving Financial Anomaly Detection via Federated Learning & Multi-Party Computation Sunpreet S. Arora Andrew Beams Panagiotis Chatzigiannis Sebastian Meiser Karan Patel ... Harshal Shah Yizhen Wang Yuhang Wu Hao-Yu Yang Mahdi Zamani FedML 11 3 0 06 Oct 2023
Chained-DP: Can We Recycle Privacy Budget? Jingyi Li Guangjing Huang Liekang Zeng Lin Chen Xu Chen FedML 20 0 0 12 Sep 2023
ULDP-FL: Federated Learning with Across Silo User-Level Differential Privacy Fumiyuki Kato Li Xiong Shun Takagi Yang Cao Masatoshi Yoshikawa FedML 17 3 0 23 Aug 2023
Compressed Private Aggregation for Scalable and Robust Federated Learning over Massive Networks Natalie Lang Nir Shlezinger Rafael G. L. DÓliveira S. E. Rouayheb FedML 65 4 0 01 Aug 2023
Private Federated Learning with Autotuned Compression Enayat Ullah Christopher A. Choquette-Choo Peter Kairouz Sewoong Oh FedML 15 6 0 20 Jul 2023
Heterogeneous Federated Learning: State-of-the-art and Research Challenges Mang Ye Xiuwen Fang Bo Du PongChi Yuen Dacheng Tao FedML AAML 33 244 0 20 Jul 2023
The importance of feature preprocessing for differentially private linear optimization Ziteng Sun A. Suresh A. Menon 14 3 0 19 Jul 2023
Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning Zachary B. Charles Nicole Mitchell Krishna Pillutla Michael Reneer Zachary Garrett FedML AI4CE 28 28 0 18 Jul 2023
Private Federated Learning in Gboard Yuanbo Zhang Daniel Ramage Zheng Xu Yanxiang Zhang Shumin Zhai Peter Kairouz FedML 25 7 0 26 Jun 2023
Randomized Quantization is All You Need for Differential Privacy in Federated Learning Yeojoon Youn Zihao Hu Juba Ziani Jacob D. Abernethy FedML 11 21 0 20 Jun 2023
AnoFel: Supporting Anonymity for Privacy-Preserving Federated Learning Ghada Almashaqbeh Zahra Ghodsi FedML 24 1 0 12 Jun 2023
Federated Learning of Gboard Language Models with Differential Privacy Zheng Xu Yanxiang Zhang Galen Andrew Christopher A. Choquette-Choo Peter Kairouz H. B. McMahan Jesse Rosenstock Yuanbo Zhang FedML 37 76 0 29 May 2023
Efficient Federated Learning with Enhanced Privacy via Lottery Ticket Pruning in Edge Computing Yi Shi Kang Wei Li Shen Jun Li Xueqian Wang Bo Yuan Song Guo 33 5 0 02 May 2023
Towards the Flatter Landscape and Better Generalization in Federated Learning under Client-level Differential Privacy Yi Shi Kang Wei Li Shen Yingqi Liu Xueqian Wang Bo Yuan Dacheng Tao FedML 28 2 0 01 May 2023
FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models Songze Li Duanyi Yao Jin Liu FedML 22 28 0 26 Apr 2023
FedBlockHealth: A Synergistic Approach to Privacy and Security in IoT-Enabled Healthcare through Federated Learning and Blockchain Nazar Waheed A. Rehman Anushka Nehra Mahnoor Farooq Nargis Tariq M. Jan Fazlullah Khan Abeer Z. Alalmaie P. Nanda 11 10 0 16 Apr 2023
Communication and Energy Efficient Wireless Federated Learning with Intrinsic Privacy Zhenxiao Zhang Yuanxiong Guo Yuguang Fang Yanmin Gong 28 4 0 15 Apr 2023
Zero-Knowledge Proof-based Practical Federated Learning on Blockchain Zhibo Xing Zijian Zhang Meng Li J. Liu Liehuang Zhu Giovanni Russello M. R. Asghar 11 17 0 12 Apr 2023
Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation Wei-Ning Chen Danni Song Ayfer Özgür Peter Kairouz FedML 13 25 0 04 Apr 2023
Make Landscape Flatter in Differentially Private Federated Learning Yi Shi Yingqi Liu Kang Wei Li Shen Xueqian Wang Dacheng Tao FedML 17 54 0 20 Mar 2023
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy Natalia Ponomareva Hussein Hazimeh Alexey Kurakin Zheng Xu Carson E. Denison H. B. McMahan Sergei Vassilvitskii Steve Chien Abhradeep Thakurta 94 167 0 01 Mar 2023
Multi-Message Shuffled Privacy in Federated Learning Antonious M. Girgis Suhas Diggavi FedML 20 8 0 22 Feb 2023
Breaking the Communication-Privacy-Accuracy Tradeoff with $f$ -Differential Privacy Richeng Jin Z. Su C. Zhong Zhaoyang Zhang Tony Q. S. Quek H. Dai FedML 19 2 0 19 Feb 2023
Balancing Privacy Protection and Interpretability in Federated Learning Zhe Li Honglong Chen Zhichen Ni Huajie Shao FedML 8 8 0 16 Feb 2023
$z$ -SignFedAvg: A Unified Stochastic Sign-based Compression for Federated Learning Zhiwei Tang Yanmeng Wang Tsung-Hui Chang FedML 19 14 0 06 Feb 2023
An Effective and Differentially Private Protocol for Secure Distributed Cardinality Estimation P. Wang Chengjin Yang Dongdong Xie Junzhou Zhao Hui Li Jing Tao Xiaohong Guan 14 2 0 04 Feb 2023
Reconstructing Individual Data Points in Federated Learning Hardened with Differential Privacy and Secure Aggregation Franziska Boenisch Adam Dziedzic R. Schuster Ali Shahin Shamsabadi Ilia Shumailov Nicolas Papernot FedML 17 20 0 09 Jan 2023
Recent Advances on Federated Learning: A Systematic Survey Bingyan Liu Nuoyan Lv Yuanchun Guo Yawen Li FedML 60 78 0 03 Jan 2023
Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy Ergute Bao Yizheng Zhu X. Xiao Y. Yang Beng Chin Ooi B. Tan Khin Mi Mi Aung FedML 23 18 0 08 Dec 2022
Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design Chuan Guo Kamalika Chaudhuri Pierre Stock Michael G. Rabbat FedML 25 7 0 08 Nov 2022
Distributed DP-Helmet: Scalable Differentially Private Non-interactive Averaging of Single Layers Moritz Kirschte Sebastian Meiser Saman Ardalan Esfandiar Mohammadi FedML 19 0 0 03 Nov 2022
PersA-FL: Personalized Asynchronous Federated Learning Taha Toghani Soomin Lee César A. Uribe FedML 32 6 0 03 Oct 2022
Unbounded Gradients in Federated Learning with Buffered Asynchronous Aggregation Taha Toghani César A. Uribe FedML 35 14 0 03 Oct 2022
Dordis: Efficient Federated Learning with Dropout-Resilient Differential Privacy Zhifeng Jiang Wei Wang Ruichuan Chen 38 6 0 26 Sep 2022
Secure Shapley Value for Cross-Silo Federated Learning (Technical Report) Shuyuan Zheng Yang Cao Masatoshi Yoshikawa FedML 58 24 0 11 Sep 2022
Private, Efficient, and Accurate: Protecting Models Trained by Multi-party Learning with Differential Privacy Wenqiang Ruan Ming Xu Wenjing Fang Li Wang Lei Wang Wei Han 32 12 0 18 Aug 2022
How Much Privacy Does Federated Learning with Secure Aggregation Guarantee? A. Elkordy Jiang Zhang Yahya H. Ezzeldin Konstantinos Psounis A. Avestimehr FedML 32 38 0 03 Aug 2022
Differentially Private Linear Bandits with Partial Distributed Feedback Fengjiao Li Xingyu Zhou Bo Ji FedML 17 13 0 12 Jul 2022
The Poisson binomial mechanism for secure and private federated learning Wei-Ning Chen Ayfer Özgür Peter Kairouz FedML 11 2 0 09 Jul 2022
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression Zhize Li Haoyu Zhao Boyue Li Yuejie Chi FedML 22 41 0 20 Jun 2022
Shuffle Gaussian Mechanism for Differential Privacy Seng Pei Liew Tsubasa Takahashi FedML 10 2 0 20 Jun 2022
Pisces: Efficient Federated Learning via Guided Asynchronous Training Zhifeng Jiang Wei Wang Baochun Li Bo-wen Li FedML 6 24 0 18 Jun 2022
On Privacy and Personalization in Cross-Silo Federated Learning Ziyu Liu Shengyuan Hu Zhiwei Steven Wu Virginia Smith FedML 20 51 0 16 Jun 2022
Distributed Differential Privacy in Multi-Armed Bandits Sayak Ray Chowdhury Xingyu Zhou 22 12 0 12 Jun 2022
Gradient Obfuscation Gives a False Sense of Security in Federated Learning Kai Yue Richeng Jin Chau-Wai Wong D. Baron H. Dai FedML 26 46 0 08 Jun 2022
Privacy Amplification via Shuffled Check-Ins Seng Pei Liew Satoshi Hasegawa Tsubasa Takahashi FedML 14 0 0 07 Jun 2022
On the (In)security of Peer-to-Peer Decentralized Machine Learning Dario Pasquini Mathilde Raynal Carmela Troncoso OOD FedML 35 19 0 17 May 2022
Protecting Data from all Parties: Combining FHE and DP in Federated Learning Arnaud Grivet Sébert Renaud Sirdey Oana Stan Cédric Gouy-Pailler FedML 11 0 0 09 May 2022
Privacy-Preserving Aggregation in Federated Learning: A Survey Ziyao Liu Jiale Guo Wenzhuo Yang Jiani Fan Kwok-Yan Lam Jun Zhao FedML 11 87 0 31 Mar 2022
Privacy-Aware Compression for Federated Data Analysis Kamalika Chaudhuri Chuan Guo Michael G. Rabbat FedML 25 27 0 15 Mar 2022