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Local Model Poisoning Attacks to Byzantine-Robust Federated Learning

Local Model Poisoning Attacks to Byzantine-Robust Federated Learning

26 November 2019
Minghong Fang
Xiaoyu Cao
Jinyuan Jia
Neil Zhenqiang Gong
    AAML
    OOD
    FedML
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Papers citing "Local Model Poisoning Attacks to Byzantine-Robust Federated Learning"

50 / 184 papers shown
Title
CrowdGuard: Federated Backdoor Detection in Federated Learning
CrowdGuard: Federated Backdoor Detection in Federated Learning
Phillip Rieger
T. Krauß
Markus Miettinen
Alexandra Dmitrienko
Ahmad-Reza Sadeghi Technical University Darmstadt
AAML
FedML
32
22
0
14 Oct 2022
Federated Learning based on Defending Against Data Poisoning Attacks in
  IoT
Federated Learning based on Defending Against Data Poisoning Attacks in IoT
Jiayin Li
Wenzhong Guo
Xingshuo Han
Jianping Cai
Ximeng Liu
AAML
83
1
0
14 Sep 2022
Unraveling the Connections between Privacy and Certified Robustness in
  Federated Learning Against Poisoning Attacks
Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks
Chulin Xie
Yunhui Long
Pin-Yu Chen
Qinbin Li
Arash Nourian
Sanmi Koyejo
Bo Li
FedML
48
13
0
08 Sep 2022
Network-Level Adversaries in Federated Learning
Network-Level Adversaries in Federated Learning
Giorgio Severi
Matthew Jagielski
Gokberk Yar
Yuxuan Wang
Alina Oprea
Cristina Nita-Rotaru
FedML
28
17
0
27 Aug 2022
MUDGUARD: Taming Malicious Majorities in Federated Learning using
  Privacy-Preserving Byzantine-Robust Clustering
MUDGUARD: Taming Malicious Majorities in Federated Learning using Privacy-Preserving Byzantine-Robust Clustering
Rui Wang
Xingkai Wang
H. Chen
Jérémie Decouchant
S. Picek
Zichen Liu
K. Liang
38
1
0
22 Aug 2022
Byzantines can also Learn from History: Fall of Centered Clipping in
  Federated Learning
Byzantines can also Learn from History: Fall of Centered Clipping in Federated Learning
Kerem Ozfatura
Emre Ozfatura
Alptekin Kupcu
Deniz Gunduz
AAML
FedML
41
13
0
21 Aug 2022
FedPerm: Private and Robust Federated Learning by Parameter Permutation
FedPerm: Private and Robust Federated Learning by Parameter Permutation
Hamid Mozaffari
Virendra J. Marathe
D. Dice
FedML
27
4
0
16 Aug 2022
Federated Learning for Medical Applications: A Taxonomy, Current Trends,
  Challenges, and Future Research Directions
Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directions
A. Rauniyar
D. Hagos
Debesh Jha
J. E. Haakegaard
Ulas Bagci
D. Rawat
Vladimir Vlassov
OOD
48
91
0
05 Aug 2022
FLDetector: Defending Federated Learning Against Model Poisoning Attacks
  via Detecting Malicious Clients
FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients
Zaixi Zhang
Xiaoyu Cao
Jin Jia
Neil Zhenqiang Gong
AAML
FedML
24
214
0
19 Jul 2022
MUD-PQFed: Towards Malicious User Detection in Privacy-Preserving
  Quantized Federated Learning
MUD-PQFed: Towards Malicious User Detection in Privacy-Preserving Quantized Federated Learning
Hua Ma
Qun Li
Yifeng Zheng
Zhi Zhang
Xiaoning Liu
Yan Gao
S. Al-Sarawi
Derek Abbott
FedML
39
3
0
19 Jul 2022
Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications
Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications
Ali Raza
Shujun Li
K. Tran
L. Koehl
Kim Duc Tran
AAML
38
3
0
18 Jul 2022
Suppressing Poisoning Attacks on Federated Learning for Medical Imaging
Suppressing Poisoning Attacks on Federated Learning for Medical Imaging
Naif Alkhunaizi
Dmitry Kamzolov
Martin Takávc
Karthik Nandakumar
OOD
26
9
0
15 Jul 2022
Enhanced Security and Privacy via Fragmented Federated Learning
Enhanced Security and Privacy via Fragmented Federated Learning
N. Jebreel
J. Domingo-Ferrer
Alberto Blanco-Justicia
David Sánchez
FedML
39
26
0
13 Jul 2022
Federated and Transfer Learning: A Survey on Adversaries and Defense
  Mechanisms
Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms
Ehsan Hallaji
R. Razavi-Far
M. Saif
AAML
FedML
27
13
0
05 Jul 2022
Backdoor Attack is a Devil in Federated GAN-based Medical Image
  Synthesis
Backdoor Attack is a Devil in Federated GAN-based Medical Image Synthesis
Ruinan Jin
Xiaoxiao Li
AAML
FedML
MedIm
44
12
0
02 Jul 2022
FLVoogd: Robust And Privacy Preserving Federated Learning
FLVoogd: Robust And Privacy Preserving Federated Learning
Yuhang Tian
Rui Wang
Yan Qiao
E. Panaousis
K. Liang
FedML
28
4
0
24 Jun 2022
DECK: Model Hardening for Defending Pervasive Backdoors
DECK: Model Hardening for Defending Pervasive Backdoors
Guanhong Tao
Yingqi Liu
Shuyang Cheng
Shengwei An
Zhuo Zhang
Qiuling Xu
Guangyu Shen
Xiangyu Zhang
AAML
26
7
0
18 Jun 2022
Edge Security: Challenges and Issues
Edge Security: Challenges and Issues
Xin Jin
Charalampos Katsis
Fan Sang
Jiahao Sun
A. Kundu
Ramana Rao Kompella
49
8
0
14 Jun 2022
Byzantine-Robust Federated Learning with Optimal Statistical Rates and
  Privacy Guarantees
Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees
Banghua Zhu
Lun Wang
Qi Pang
Shuai Wang
Jiantao Jiao
D. Song
Michael I. Jordan
FedML
98
30
0
24 May 2022
Robust Quantity-Aware Aggregation for Federated Learning
Robust Quantity-Aware Aggregation for Federated Learning
Jingwei Yi
Fangzhao Wu
Huishuai Zhang
Bin Zhu
Tao Qi
Guangzhong Sun
Xing Xie
FedML
35
2
0
22 May 2022
PoisonedEncoder: Poisoning the Unlabeled Pre-training Data in
  Contrastive Learning
PoisonedEncoder: Poisoning the Unlabeled Pre-training Data in Contrastive Learning
Hongbin Liu
Jinyuan Jia
Neil Zhenqiang Gong
33
34
0
13 May 2022
Federated Multi-Armed Bandits Under Byzantine Attacks
Federated Multi-Armed Bandits Under Byzantine Attacks
Artun Saday
Ilker Demirel
Yiğit Yıldırım
Cem Tekin
AAML
37
13
0
09 May 2022
Backdoor Attacks in Federated Learning by Rare Embeddings and Gradient
  Ensembling
Backdoor Attacks in Federated Learning by Rare Embeddings and Gradient Ensembling
Kiyoon Yoo
Nojun Kwak
SILM
AAML
FedML
25
19
0
29 Apr 2022
Poisoning Deep Learning Based Recommender Model in Federated Learning
  Scenarios
Poisoning Deep Learning Based Recommender Model in Federated Learning Scenarios
Dazhong Rong
Qinming He
Jianhai Chen
FedML
27
41
0
26 Apr 2022
Adversarial Analysis of the Differentially-Private Federated Learning in
  Cyber-Physical Critical Infrastructures
Adversarial Analysis of the Differentially-Private Federated Learning in Cyber-Physical Critical Infrastructures
Md Tamjid Hossain
S. Badsha
Hung M. La
Haoting Shen
Shafkat Islam
Ibrahim Khalil
X. Yi
AAML
29
3
0
06 Apr 2022
FedRecAttack: Model Poisoning Attack to Federated Recommendation
FedRecAttack: Model Poisoning Attack to Federated Recommendation
Dazhong Rong
Shuai Ye
Ruoyan Zhao
Hon Ning Yuen
Jianhai Chen
Qinming He
AAML
FedML
24
57
0
01 Apr 2022
MixNN: A design for protecting deep learning models
MixNN: A design for protecting deep learning models
Chao Liu
Hao Chen
Yusen Wu
Rui Jin
12
0
0
28 Mar 2022
Latency Optimization for Blockchain-Empowered Federated Learning in
  Multi-Server Edge Computing
Latency Optimization for Blockchain-Empowered Federated Learning in Multi-Server Edge Computing
Dinh C. Nguyen
Seyyedali Hosseinalipour
David J. Love
P. Pathirana
Christopher G. Brinton
34
47
0
18 Mar 2022
MPAF: Model Poisoning Attacks to Federated Learning based on Fake
  Clients
MPAF: Model Poisoning Attacks to Federated Learning based on Fake Clients
Xiaoyu Cao
Neil Zhenqiang Gong
26
108
0
16 Mar 2022
Low-Loss Subspace Compression for Clean Gains against Multi-Agent
  Backdoor Attacks
Low-Loss Subspace Compression for Clean Gains against Multi-Agent Backdoor Attacks
Siddhartha Datta
N. Shadbolt
AAML
32
6
0
07 Mar 2022
More is Better (Mostly): On the Backdoor Attacks in Federated Graph
  Neural Networks
More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks
Jing Xu
Rui Wang
Stefanos Koffas
K. Liang
S. Picek
FedML
AAML
39
25
0
07 Feb 2022
Securing Federated Sensitive Topic Classification against Poisoning
  Attacks
Securing Federated Sensitive Topic Classification against Poisoning Attacks
Tianyue Chu
Álvaro García-Recuero
Costas Iordanou
Georgios Smaragdakis
Nikolaos Laoutaris
51
9
0
31 Jan 2022
Backdoors Stuck At The Frontdoor: Multi-Agent Backdoor Attacks That
  Backfire
Backdoors Stuck At The Frontdoor: Multi-Agent Backdoor Attacks That Backfire
Siddhartha Datta
N. Shadbolt
AAML
38
7
0
28 Jan 2022
FedComm: Federated Learning as a Medium for Covert Communication
FedComm: Federated Learning as a Medium for Covert Communication
Dorjan Hitaj
Giulio Pagnotta
Briland Hitaj
Fernando Perez-Cruz
L. Mancini
FedML
32
10
0
21 Jan 2022
Survey on Federated Learning Threats: concepts, taxonomy on attacks and
  defences, experimental study and challenges
Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challenges
Nuria Rodríguez-Barroso
Daniel Jiménez López
M. V. Luzón
Francisco Herrera
Eugenio Martínez-Cámara
FedML
37
213
0
20 Jan 2022
Security for Machine Learning-based Software Systems: a survey of
  threats, practices and challenges
Security for Machine Learning-based Software Systems: a survey of threats, practices and challenges
Huaming Chen
Muhammad Ali Babar
AAML
42
22
0
12 Jan 2022
LoMar: A Local Defense Against Poisoning Attack on Federated Learning
LoMar: A Local Defense Against Poisoning Attack on Federated Learning
Xingyu Li
Zhe Qu
Shangqing Zhao
Bo Tang
Zhuo Lu
Yao-Hong Liu
AAML
41
92
0
08 Jan 2022
DeepSight: Mitigating Backdoor Attacks in Federated Learning Through
  Deep Model Inspection
DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection
Phillip Rieger
T. D. Nguyen
Markus Miettinen
A. Sadeghi
FedML
AAML
41
152
0
03 Jan 2022
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive
  Survey
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey
Shangwei Guo
Xu Zhang
Feiyu Yang
Tianwei Zhang
Yan Gan
Tao Xiang
Yang Liu
FedML
31
9
0
19 Dec 2021
Analysis and Evaluation of Synchronous and Asynchronous FLchain
Analysis and Evaluation of Synchronous and Asynchronous FLchain
F. Wilhelmi
L. Giupponi
Paolo Dini
25
5
0
15 Dec 2021
SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with
  Sparsification
SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification
Ashwinee Panda
Saeed Mahloujifar
A. Bhagoji
Supriyo Chakraborty
Prateek Mittal
FedML
AAML
17
85
0
12 Dec 2021
ARFED: Attack-Resistant Federated averaging based on outlier elimination
ARFED: Attack-Resistant Federated averaging based on outlier elimination
Ece Isik Polat
Gorkem Polat
Altan Koçyiğit
AAML
FedML
41
10
0
08 Nov 2021
DFL: High-Performance Blockchain-Based Federated Learning
DFL: High-Performance Blockchain-Based Federated Learning
Yongding Tian
Zhuoran Guo
Jiaxuan Zhang
Zaid Al-Ars
OOD
FedML
31
10
0
28 Oct 2021
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in
  Federated Learning from a Client Perspective
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective
Jingwei Sun
Ang Li
Louis DiValentin
Amin Hassanzadeh
Yiran Chen
H. Li
FedML
OOD
AAML
36
76
0
26 Oct 2021
MANDERA: Malicious Node Detection in Federated Learning via Ranking
MANDERA: Malicious Node Detection in Federated Learning via Ranking
Wanchuang Zhu
Benjamin Zi Hao Zhao
Simon Luo
Tongliang Liu
Kefeng Deng
AAML
29
8
0
22 Oct 2021
Bristle: Decentralized Federated Learning in Byzantine, Non-i.i.d.
  Environments
Bristle: Decentralized Federated Learning in Byzantine, Non-i.i.d. Environments
Joost Verbraeken
M. Vos
J. Pouwelse
31
4
0
21 Oct 2021
PipAttack: Poisoning Federated Recommender Systems forManipulating Item
  Promotion
PipAttack: Poisoning Federated Recommender Systems forManipulating Item Promotion
Shijie Zhang
Hongzhi Yin
Tong Chen
Zi Huang
Quoc Viet Hung Nguyen
Li-zhen Cui
FedML
AAML
19
96
0
21 Oct 2021
TESSERACT: Gradient Flip Score to Secure Federated Learning Against
  Model Poisoning Attacks
TESSERACT: Gradient Flip Score to Secure Federated Learning Against Model Poisoning Attacks
Atul Sharma
Wei Chen
Joshua C. Zhao
Qiang Qiu
Somali Chaterji
S. Bagchi
FedML
AAML
54
5
0
19 Oct 2021
SecFL: Confidential Federated Learning using TEEs
SecFL: Confidential Federated Learning using TEEs
D. Quoc
Christof Fetzer
FedML
24
16
0
03 Oct 2021
DeSMP: Differential Privacy-exploited Stealthy Model Poisoning Attacks
  in Federated Learning
DeSMP: Differential Privacy-exploited Stealthy Model Poisoning Attacks in Federated Learning
Md Tamjid Hossain
Shafkat Islam
S. Badsha
Haoting Shen
AAML
55
41
0
21 Sep 2021
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