ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2203.17005
  4. Cited By
Privacy-Preserving Aggregation in Federated Learning: A Survey

Privacy-Preserving Aggregation in Federated Learning: A Survey

31 March 2022
Ziyao Liu
Jiale Guo
Wenzhuo Yang
Jiani Fan
Kwok-Yan Lam
Jun Zhao
    FedML
ArXivPDFHTML

Papers citing "Privacy-Preserving Aggregation in Federated Learning: A Survey"

21 / 21 papers shown
Title
Clustering-Based Evolutionary Federated Multiobjective Optimization and Learning
Clustering-Based Evolutionary Federated Multiobjective Optimization and Learning
Chengui Xiao
Songbai Liu
FedML
70
0
0
29 Apr 2025
A Survey on Federated Analytics: Taxonomy, Enabling Techniques, Applications and Open Issues
A Survey on Federated Analytics: Taxonomy, Enabling Techniques, Applications and Open Issues
Zibo Wang
Haichao Ji
Yifei Zhu
Dan Wang
Zhu Han
51
1
0
19 Apr 2024
Privacy-Preserving Federated Unlearning with Certified Client Removal
Privacy-Preserving Federated Unlearning with Certified Client Removal
Ziyao Liu
Huanyi Ye
Yu Jiang
Jiyuan Shen
Jiale Guo
Ivan Tjuawinata
Kwok-Yan Lam
MU
27
5
0
15 Apr 2024
Threats, Attacks, and Defenses in Machine Unlearning: A Survey
Threats, Attacks, and Defenses in Machine Unlearning: A Survey
Ziyao Liu
Huanyi Ye
Chen Chen
Yongsen Zheng
K. Lam
AAML
MU
32
28
0
20 Mar 2024
Harnessing the Power of Federated Learning in Federated Contextual
  Bandits
Harnessing the Power of Federated Learning in Federated Contextual Bandits
Chengshuai Shi
Ruida Zhou
Kun Yang
Cong Shen
FedML
21
0
0
26 Dec 2023
Edge Learning for 6G-enabled Internet of Things: A Comprehensive Survey
  of Vulnerabilities, Datasets, and Defenses
Edge Learning for 6G-enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses
M. Ferrag
Othmane Friha
B. Kantarci
Norbert Tihanyi
Lucas C. Cordeiro
Merouane Debbah
Djallel Hamouda
Muna Al-Hawawreh
K. Choo
23
43
0
17 Jun 2023
Marvel DC: A Blockchain-Based Decentralized and Incentive-Compatible
  Distributed Computing Protocol
Marvel DC: A Blockchain-Based Decentralized and Incentive-Compatible Distributed Computing Protocol
Conor McMenamin
Vanesa Daza
19
1
0
28 Jul 2022
BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine
  Learning
BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine Learning
A. Mondal
Harpreet Virk
Debayan Gupta
32
15
0
06 Feb 2022
LightSecAgg: a Lightweight and Versatile Design for Secure Aggregation
  in Federated Learning
LightSecAgg: a Lightweight and Versatile Design for Secure Aggregation in Federated Learning
Jinhyun So
Chaoyang He
Chien-Sheng Yang
Songze Li
Qian-long Yu
Ramy E. Ali
Başak Güler
Salman Avestimehr
FedML
64
164
0
29 Sep 2021
MixNN: Protection of Federated Learning Against Inference Attacks by
  Mixing Neural Network Layers
MixNN: Protection of Federated Learning Against Inference Attacks by Mixing Neural Network Layers
A. Boutet
Thomas LeBrun
Jan Aalmoes
Adrien Baud
FedML
52
17
0
26 Sep 2021
Dubhe: Towards Data Unbiasedness with Homomorphic Encryption in
  Federated Learning Client Selection
Dubhe: Towards Data Unbiasedness with Homomorphic Encryption in Federated Learning Client Selection
Shulai Zhang
Zirui Li
Quan Chen
Wenli Zheng
Jingwen Leng
M. Guo
FedML
57
32
0
08 Sep 2021
Secure Neuroimaging Analysis using Federated Learning with Homomorphic
  Encryption
Secure Neuroimaging Analysis using Federated Learning with Homomorphic Encryption
Dimitris Stripelis
Hamza Saleem
Tanmay Ghai
Nikhil J. Dhinagar
Umang Gupta
...
Greg Ver Steeg
Srivatsan Ravi
Muhammad Naveed
Paul M. Thompson
J. Ambite
FedML
44
53
0
07 Aug 2021
Towards Personalized Federated Learning
Towards Personalized Federated Learning
A. Tan
Han Yu
Li-zhen Cui
Qiang Yang
FedML
AI4CE
209
840
0
01 Mar 2021
Federated Learning with Local Differential Privacy: Trade-offs between
  Privacy, Utility, and Communication
Federated Learning with Local Differential Privacy: Trade-offs between Privacy, Utility, and Communication
Muah Kim
Onur Gunlu
Rafael F. Schaefer
FedML
107
118
0
09 Feb 2021
Information Theoretic Secure Aggregation with User Dropouts
Information Theoretic Secure Aggregation with User Dropouts
Yizhou Zhao
Hua Sun
FedML
59
67
0
19 Jan 2021
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping
Xiaoyu Cao
Minghong Fang
Jia Liu
Neil Zhenqiang Gong
FedML
108
611
0
27 Dec 2020
Towards Communication-efficient and Attack-Resistant Federated Edge
  Learning for Industrial Internet of Things
Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things
Yi Liu
Ruihui Zhao
Jiawen Kang
A. Yassine
Dusit Niyato
Jia-Jie Peng
FedML
69
35
0
08 Dec 2020
Privacy and Robustness in Federated Learning: Attacks and Defenses
Privacy and Robustness in Federated Learning: Attacks and Defenses
Lingjuan Lyu
Han Yu
Xingjun Ma
Chen Chen
Lichao Sun
Jun Zhao
Qiang Yang
Philip S. Yu
FedML
180
355
0
07 Dec 2020
FedML: A Research Library and Benchmark for Federated Machine Learning
FedML: A Research Library and Benchmark for Federated Machine Learning
Chaoyang He
Songze Li
Jinhyun So
Xiao Zeng
Mi Zhang
...
Yang Liu
Ramesh Raskar
Qiang Yang
M. Annavaram
Salman Avestimehr
FedML
168
564
0
27 Jul 2020
IBM Federated Learning: an Enterprise Framework White Paper V0.1
IBM Federated Learning: an Enterprise Framework White Paper V0.1
Heiko Ludwig
Nathalie Baracaldo
Gegi Thomas
Yi Zhou
Ali Anwar
...
Sean Laguna
Mikhail Yurochkin
Mayank Agarwal
Ebube Chuba
Annie Abay
FedML
131
157
0
22 Jul 2020
Threats to Federated Learning: A Survey
Threats to Federated Learning: A Survey
Lingjuan Lyu
Han Yu
Qiang Yang
FedML
196
434
0
04 Mar 2020
1