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FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping

FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping

27 December 2020
Xiaoyu Cao
Minghong Fang
Jia Liu
Neil Zhenqiang Gong
    FedML
ArXivPDFHTML

Papers citing "FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping"

50 / 71 papers shown
Title
Trial and Trust: Addressing Byzantine Attacks with Comprehensive Defense Strategy
Trial and Trust: Addressing Byzantine Attacks with Comprehensive Defense Strategy
Gleb Molodtsov
Daniil Medyakov
Sergey Skorik
Nikolas Khachaturov
Shahane Tigranyan
Vladimir Aletov
A. Avetisyan
Martin Takáč
Aleksandr Beznosikov
AAML
32
0
0
12 May 2025
Traceback of Poisoning Attacks to Retrieval-Augmented Generation
Traceback of Poisoning Attacks to Retrieval-Augmented Generation
Baolei Zhang
Haoran Xin
Minghong Fang
Zhuqing Liu
Biao Yi
Tong Li
Zheli Liu
SILM
AAML
64
0
0
30 Apr 2025
Moss: Proxy Model-based Full-Weight Aggregation in Federated Learning with Heterogeneous Models
Y. Cai
Ziqi Zhang
Ding Li
Yao Guo
Xiangqun Chen
50
0
0
13 Mar 2025
Detecting Backdoor Attacks in Federated Learning via Direction Alignment Inspection
Detecting Backdoor Attacks in Federated Learning via Direction Alignment Inspection
Jiahao Xu
Zikai Zhang
Rui Hu
AAML
FedML
Presented at ResearchTrend Connect | FedML on 28 Mar 2025
145
0
0
11 Mar 2025
SMTFL: Secure Model Training to Untrusted Participants in Federated Learning
SMTFL: Secure Model Training to Untrusted Participants in Federated Learning
Zhihui Zhao
Xiaorong Dong
Yimo Ren
Jianhua Wang
Dan Yu
Hongsong Zhu
Yongle Chen
79
0
0
24 Feb 2025
FedCC: Robust Federated Learning against Model Poisoning Attacks
FedCC: Robust Federated Learning against Model Poisoning Attacks
Hyejun Jeong
H. Son
Seohu Lee
Jayun Hyun
T. Chung
FedML
61
5
0
20 Feb 2025
Decoding FL Defenses: Systemization, Pitfalls, and Remedies
Decoding FL Defenses: Systemization, Pitfalls, and Remedies
M. A. Khan
Virat Shejwalkar
Yasra Chandio
Amir Houmansadr
Fatima M. Anwar
AAML
38
0
0
03 Feb 2025
Poisoning Attacks and Defenses to Federated Unlearning
Poisoning Attacks and Defenses to Federated Unlearning
Wenbin Wang
Qiwen Ma
Zifan Zhang
Yuchen Liu
Zhuqing Liu
Minghong Fang
MU
FedML
77
2
0
29 Jan 2025
Do We Really Need to Design New Byzantine-robust Aggregation Rules?
Do We Really Need to Design New Byzantine-robust Aggregation Rules?
Minghong Fang
Seyedsina Nabavirazavi
Zhuqing Liu
Wei Sun
S. Iyengar
Haibo Yang
AAML
OOD
76
6
0
29 Jan 2025
ByzSFL: Achieving Byzantine-Robust Secure Federated Learning with Zero-Knowledge Proofs
ByzSFL: Achieving Byzantine-Robust Secure Federated Learning with Zero-Knowledge Proofs
Yongming Fan
Rui Zhu
Zihao Wang
Chenghong Wang
Haixu Tang
Ye Dong
Hyunghoon Cho
Lucila Ohno-Machado
43
0
0
12 Jan 2025
SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version)
SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version)
Phillip Rieger
Alessandro Pegoraro
Kavita Kumari
Tigist Abera
Jonathan Knauer
A. Sadeghi
AAML
48
2
0
11 Jan 2025
Identify Backdoored Model in Federated Learning via Individual
  Unlearning
Identify Backdoored Model in Federated Learning via Individual Unlearning
Jiahao Xu
Zikai Zhang
Rui Hu
FedML
AAML
60
1
0
01 Nov 2024
Byzantine-Robust Aggregation for Securing Decentralized Federated
  Learning
Byzantine-Robust Aggregation for Securing Decentralized Federated Learning
Diego Cajaraville-Aboy
Ana Fernández-Vilas
R. Redondo
Manuel Fernández-Veiga
25
2
0
26 Sep 2024
Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework
Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework
Zilinghan Li
Shilan He
Ze Yang
Minseok Ryu
Kibaek Kim
Ravi K. Madduri
FedML
52
5
0
17 Sep 2024
Federated Learning for Smart Grid: A Survey on Applications and
  Potential Vulnerabilities
Federated Learning for Smart Grid: A Survey on Applications and Potential Vulnerabilities
Zikai Zhang
Suman Rath
Jiaohao Xu
Tingsong Xiao
48
1
0
16 Sep 2024
Buffer-based Gradient Projection for Continual Federated Learning
Buffer-based Gradient Projection for Continual Federated Learning
Shenghong Dai
Jy-yong Sohn
Yicong Chen
S. Alam
Ravikumar Balakrishnan
Suman Banerjee
N. Himayat
Kangwook Lee
FedML
75
2
0
03 Sep 2024
Achieving Byzantine-Resilient Federated Learning via Layer-Adaptive
  Sparsified Model Aggregation
Achieving Byzantine-Resilient Federated Learning via Layer-Adaptive Sparsified Model Aggregation
Jiahao Xu
Zikai Zhang
Rui Hu
44
4
0
02 Sep 2024
LiD-FL: Towards List-Decodable Federated Learning
LiD-FL: Towards List-Decodable Federated Learning
Hong Liu
Liren Shan
Han Bao
Ronghui You
Yuhao Yi
Jiancheng Lv
FedML
33
0
0
09 Aug 2024
A Learning-Based Attack Framework to Break SOTA Poisoning Defenses in
  Federated Learning
A Learning-Based Attack Framework to Break SOTA Poisoning Defenses in Federated Learning
Yuxin Yang
Qiang Li
Chenfei Nie
Yuan Hong
Meng Pang
Binghui Wang
AAML
FedML
37
1
0
21 Jul 2024
Partner in Crime: Boosting Targeted Poisoning Attacks against Federated Learning
Partner in Crime: Boosting Targeted Poisoning Attacks against Federated Learning
Shihua Sun
Shridatt Sugrim
Angelos Stavrou
Haining Wang
AAML
60
1
0
13 Jul 2024
BoBa: Boosting Backdoor Detection through Data Distribution Inference in
  Federated Learning
BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning
Ning Wang
Shanghao Shi
Yang Xiao
Yimin Chen
Y. T. Hou
W. Lou
FedML
AAML
36
1
0
12 Jul 2024
DART: A Solution for Decentralized Federated Learning Model Robustness
  Analysis
DART: A Solution for Decentralized Federated Learning Model Robustness Analysis
Chao Feng
Alberto Huertas Celdrán
Jan von der Assen
Enrique Tomás Martínez Beltrán
Gérome Bovet
Burkhard Stiller
OOD
AAML
54
8
0
11 Jul 2024
Securing Distributed Network Digital Twin Systems Against Model Poisoning Attacks
Securing Distributed Network Digital Twin Systems Against Model Poisoning Attacks
Zifan Zhang
Minghong Fang
Mingzhe Chen
Gaolei Li
Xi Lin
Yuchen Liu
AAML
45
3
0
02 Jul 2024
Asynchronous Byzantine Federated Learning
Asynchronous Byzantine Federated Learning
Bart Cox
Abele Malan
Lydia Y. Chen
Jérémie Decouchant
44
1
0
03 Jun 2024
ACE: A Model Poisoning Attack on Contribution Evaluation Methods in
  Federated Learning
ACE: A Model Poisoning Attack on Contribution Evaluation Methods in Federated Learning
Zhangchen Xu
Fengqing Jiang
Luyao Niu
Jinyuan Jia
Bo Li
Radha Poovendran
FedML
49
1
0
31 May 2024
Federated Behavioural Planes: Explaining the Evolution of Client
  Behaviour in Federated Learning
Federated Behavioural Planes: Explaining the Evolution of Client Behaviour in Federated Learning
Dario Fenoglio
Gabriele Dominici
Pietro Barbiero
Alberto Tonda
M. Gjoreski
Marc Langheinrich
FedML
31
0
0
24 May 2024
Understanding Server-Assisted Federated Learning in the Presence of
  Incomplete Client Participation
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation
Haibo Yang
Pei-Yuan Qiu
Prashant Khanduri
Minghong Fang
Jia Liu
FedML
40
1
0
04 May 2024
Poisoning Attacks on Federated Learning-based Wireless Traffic Prediction
Poisoning Attacks on Federated Learning-based Wireless Traffic Prediction
Zifan Zhang
Minghong Fang
Jiayuan Huang
Yuchen Liu
AAML
43
8
0
22 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
29
5
0
15 Apr 2024
Precision Guided Approach to Mitigate Data Poisoning Attacks in
  Federated Learning
Precision Guided Approach to Mitigate Data Poisoning Attacks in Federated Learning
Naveen Kumar
Krishna Mohan
Aravind Machiry
AAML
34
1
0
05 Apr 2024
FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive
  Models
FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive Models
Younghan Lee
Yungi Cho
Woorim Han
Ho Bae
Y. Paek
FedML
AAML
27
2
0
05 Mar 2024
Towards Fair, Robust and Efficient Client Contribution Evaluation in
  Federated Learning
Towards Fair, Robust and Efficient Client Contribution Evaluation in Federated Learning
Meiying Zhang
Huan Zhao
Sheldon C Ebron
Kan Yang
FedML
16
2
0
06 Feb 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
Wenqi Wei
Ling Liu
28
16
0
02 Feb 2024
Voyager: MTD-Based Aggregation Protocol for Mitigating Poisoning Attacks
  on DFL
Voyager: MTD-Based Aggregation Protocol for Mitigating Poisoning Attacks on DFL
Chao Feng
Alberto Huertas Celdrán
Michael Vuong
Gérome Bovet
Burkhard Stiller
AAML
24
1
0
12 Oct 2023
A Survey for Federated Learning Evaluations: Goals and Measures
A Survey for Federated Learning Evaluations: Goals and Measures
Di Chai
Leye Wang
Liu Yang
Junxue Zhang
Kai Chen
Qian Yang
ELM
FedML
17
21
0
23 Aug 2023
A Four-Pronged Defense Against Byzantine Attacks in Federated Learning
A Four-Pronged Defense Against Byzantine Attacks in Federated Learning
Wei Wan
Shengshan Hu
Minghui Li
Jianrong Lu
Longling Zhang
Leo Yu Zhang
Hai Jin
AAML
FedML
29
20
0
07 Aug 2023
Analysis and Optimization of Wireless Federated Learning with Data
  Heterogeneity
Analysis and Optimization of Wireless Federated Learning with Data Heterogeneity
Xu Han
Jun Li
Wen Chen
Zhen Mei
Kang Wei
Ming Ding
H. Vincent Poor
28
2
0
04 Aug 2023
A First Order Meta Stackelberg Method for Robust Federated Learning
A First Order Meta Stackelberg Method for Robust Federated Learning
Yunian Pan
Tao Li
Henger Li
Tianyi Xu
Zizhan Zheng
Quanyan Zhu
FedML
29
10
0
23 Jun 2023
Avoid Adversarial Adaption in Federated Learning by Multi-Metric
  Investigations
Avoid Adversarial Adaption in Federated Learning by Multi-Metric Investigations
T. Krauß
Alexandra Dmitrienko
AAML
27
4
0
06 Jun 2023
Collaborative Learning via Prediction Consensus
Collaborative Learning via Prediction Consensus
Dongyang Fan
Celestine Mendler-Dünner
Martin Jaggi
FedML
29
7
0
29 May 2023
Protecting Federated Learning from Extreme Model Poisoning Attacks via
  Multidimensional Time Series Anomaly Detection
Protecting Federated Learning from Extreme Model Poisoning Attacks via Multidimensional Time Series Anomaly Detection
Edoardo Gabrielli
Dimitri Belli
Vittorio Miori
Gabriele Tolomei
AAML
13
4
0
29 Mar 2023
A Survey of Trustworthy Federated Learning with Perspectives on
  Security, Robustness, and Privacy
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy
Yifei Zhang
Dun Zeng
Jinglong Luo
Zenglin Xu
Irwin King
FedML
84
47
0
21 Feb 2023
BayBFed: Bayesian Backdoor Defense for Federated Learning
BayBFed: Bayesian Backdoor Defense for Federated Learning
Kavita Kumari
Phillip Rieger
Hossein Fereidooni
Murtuza Jadliwala
A. Sadeghi
AAML
FedML
26
31
0
23 Jan 2023
"Real Attackers Don't Compute Gradients": Bridging the Gap Between
  Adversarial ML Research and Practice
"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice
Giovanni Apruzzese
Hyrum S. Anderson
Savino Dambra
D. Freeman
Fabio Pierazzi
Kevin A. Roundy
AAML
31
75
0
29 Dec 2022
XMAM:X-raying Models with A Matrix to Reveal Backdoor Attacks for
  Federated Learning
XMAM:X-raying Models with A Matrix to Reveal Backdoor Attacks for Federated Learning
Jianyi Zhang
Fangjiao Zhang
Qichao Jin
Zhiqiang Wang
Xiaodong Lin
X. Hei
AAML
FedML
32
0
0
28 Dec 2022
FairRoad: Achieving Fairness for Recommender Systems with Optimized
  Antidote Data
FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data
Minghong Fang
Jia-Wei Liu
Michinari Momma
Yi Sun
22
4
0
13 Dec 2022
FedCut: A Spectral Analysis Framework for Reliable Detection of
  Byzantine Colluders
FedCut: A Spectral Analysis Framework for Reliable Detection of Byzantine Colluders
Hanlin Gu
Lixin Fan
Xingxing Tang
Qiang Yang
AAML
FedML
20
1
0
24 Nov 2022
Robust Distributed Learning Against Both Distributional Shifts and
  Byzantine Attacks
Robust Distributed Learning Against Both Distributional Shifts and Byzantine Attacks
Guanqiang Zhou
Ping Xu
Yue Wang
Zhi Tian
OOD
FedML
28
4
0
29 Oct 2022
FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated
  Learning
FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning
Kaiyuan Zhang
Guanhong Tao
Qiuling Xu
Shuyang Cheng
Shengwei An
...
Shiwei Feng
Guangyu Shen
Pin-Yu Chen
Shiqing Ma
Xiangyu Zhang
FedML
40
51
0
23 Oct 2022
FedRecover: Recovering from Poisoning Attacks in Federated Learning
  using Historical Information
FedRecover: Recovering from Poisoning Attacks in Federated Learning using Historical Information
Xiaoyu Cao
Jinyuan Jia
Zaixi Zhang
Neil Zhenqiang Gong
FedML
MU
AAML
21
73
0
20 Oct 2022
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