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How To Backdoor Federated Learning

How To Backdoor Federated Learning

2 July 2018
Eugene Bagdasaryan
Andreas Veit
Yiqing Hua
D. Estrin
Vitaly Shmatikov
    SILM
    FedML
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Papers citing "How To Backdoor Federated Learning"

50 / 349 papers shown
Title
The Impact of Data Distribution on Fairness and Robustness in Federated
  Learning
The Impact of Data Distribution on Fairness and Robustness in Federated Learning
Mustafa Safa Ozdayi
Murat Kantarcioglu
FedML
OOD
24
4
0
29 Nov 2021
Anomaly Localization in Model Gradients Under Backdoor Attacks Against
  Federated Learning
Anomaly Localization in Model Gradients Under Backdoor Attacks Against Federated Learning
Z. Bilgin
FedML
AAML
24
1
0
29 Nov 2021
A General Framework for Defending Against Backdoor Attacks via Influence
  Graph
A General Framework for Defending Against Backdoor Attacks via Influence Graph
Xiaofei Sun
Jiwei Li
Xiaoya Li
Ziyao Wang
Tianwei Zhang
Han Qiu
Fei Wu
Chun Fan
AAML
TDI
24
5
0
29 Nov 2021
The Internet of Federated Things (IoFT): A Vision for the Future and
  In-depth Survey of Data-driven Approaches for Federated Learning
The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning
Raed Al Kontar
Naichen Shi
Xubo Yue
Seokhyun Chung
E. Byon
...
Chinedum Okwudire
Garvesh Raskutti
R. Saigal
Karandeep Singh
Ye Zhisheng
FedML
49
51
0
09 Nov 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
46
10
0
08 Nov 2021
Resource-Efficient Federated Learning
Resource-Efficient Federated Learning
A. Abdelmoniem
Atal Narayan Sahu
Marco Canini
Suhaib A. Fahmy
FedML
37
55
0
01 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
77
0
26 Oct 2021
Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving
  Adversarial Outcomes
Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes
Sanghyun Hong
Michael-Andrei Panaitescu-Liess
Yigitcan Kaya
Tudor Dumitras
MQ
60
13
0
26 Oct 2021
Ensemble Federated Adversarial Training with Non-IID data
Ensemble Federated Adversarial Training with Non-IID data
Shuang Luo
Didi Zhu
Zexi Li
Chao-Xiang Wu
FedML
33
7
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
22
96
0
21 Oct 2021
Resource-constrained Federated Edge Learning with Heterogeneous Data:
  Formulation and Analysis
Resource-constrained Federated Edge Learning with Heterogeneous Data: Formulation and Analysis
Yi Liu
Yuanshao Zhu
James J. Q. Yu
FedML
32
28
0
14 Oct 2021
Federated Phish Bowl: LSTM-Based Decentralized Phishing Email Detection
Federated Phish Bowl: LSTM-Based Decentralized Phishing Email Detection
Yuwei Sun
Ng Chong
H. Ochiai
FedML
21
6
0
12 Oct 2021
Paving the Way for Distributed Artificial Intelligence over the Air
Paving the Way for Distributed Artificial Intelligence over the Air
Guoqing Ma
Shuping Dang
Chuanting Zhang
B. Shihada
27
3
0
24 Sep 2021
Backdoor Attacks on Federated Learning with Lottery Ticket Hypothesis
Backdoor Attacks on Federated Learning with Lottery Ticket Hypothesis
Zeyuan Yin
Ye Yuan
Panfeng Guo
Pan Zhou
FedML
45
7
0
22 Sep 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
Source Inference Attacks in Federated Learning
Source Inference Attacks in Federated Learning
Hongsheng Hu
Z. Salcic
Lichao Sun
Gillian Dobbie
Xuyun Zhang
32
79
0
13 Sep 2021
Quantization Backdoors to Deep Learning Commercial Frameworks
Quantization Backdoors to Deep Learning Commercial Frameworks
Hua Ma
Huming Qiu
Yansong Gao
Zhi-Li Zhang
A. Abuadbba
Minhui Xue
Anmin Fu
Jiliang Zhang
S. Al-Sarawi
Derek Abbott
MQ
43
19
0
20 Aug 2021
Aegis: A Trusted, Automatic and Accurate Verification Framework for
  Vertical Federated Learning
Aegis: A Trusted, Automatic and Accurate Verification Framework for Vertical Federated Learning
Cengguang Zhang
Junxue Zhang
Di Chai
Kai Chen
FedML
27
5
0
16 Aug 2021
An Operator Splitting View of Federated Learning
An Operator Splitting View of Federated Learning
Saber Malekmohammadi
Kiarash Shaloudegi
Zeou Hu
Yaoliang Yu
FedML
31
2
0
12 Aug 2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
Runhua Xu
Nathalie Baracaldo
J. Joshi
32
99
0
10 Aug 2021
Fed-BEV: A Federated Learning Framework for Modelling Energy Consumption
  of Battery Electric Vehicles
Fed-BEV: A Federated Learning Framework for Modelling Energy Consumption of Battery Electric Vehicles
Mingming Liu
27
14
0
05 Aug 2021
Advances in adversarial attacks and defenses in computer vision: A
  survey
Advances in adversarial attacks and defenses in computer vision: A survey
Naveed Akhtar
Ajmal Mian
Navid Kardan
M. Shah
AAML
41
236
0
01 Aug 2021
BadEncoder: Backdoor Attacks to Pre-trained Encoders in Self-Supervised
  Learning
BadEncoder: Backdoor Attacks to Pre-trained Encoders in Self-Supervised Learning
Jinyuan Jia
Yupei Liu
Neil Zhenqiang Gong
SILM
SSL
47
152
0
01 Aug 2021
Decentralized Deep Learning for Multi-Access Edge Computing: A Survey on
  Communication Efficiency and Trustworthiness
Decentralized Deep Learning for Multi-Access Edge Computing: A Survey on Communication Efficiency and Trustworthiness
Yuwei Sun
H. Ochiai
Hiroshi Esaki
FedML
79
45
0
30 Jul 2021
FedLab: A Flexible Federated Learning Framework
FedLab: A Flexible Federated Learning Framework
Dun Zeng
Siqi Liang
Xiangjing Hu
Hui Wang
Zenglin Xu
FedML
15
107
0
24 Jul 2021
Spinning Sequence-to-Sequence Models with Meta-Backdoors
Eugene Bagdasaryan
Vitaly Shmatikov
SILM
AAML
43
8
0
22 Jul 2021
A Field Guide to Federated Optimization
A Field Guide to Federated Optimization
Jianyu Wang
Zachary B. Charles
Zheng Xu
Gauri Joshi
H. B. McMahan
...
Mi Zhang
Tong Zhang
Chunxiang Zheng
Chen Zhu
Wennan Zhu
FedML
187
412
0
14 Jul 2021
Survey: Leakage and Privacy at Inference Time
Survey: Leakage and Privacy at Inference Time
Marija Jegorova
Chaitanya Kaul
Charlie Mayor
Alison Q. OÑeil
Alexander Weir
Roderick Murray-Smith
Sotirios A. Tsaftaris
PILM
MIACV
33
71
0
04 Jul 2021
Byzantine-robust Federated Learning through Spatial-temporal Analysis of
  Local Model Updates
Byzantine-robust Federated Learning through Spatial-temporal Analysis of Local Model Updates
Zhuohang Li
Luyang Liu
Jiaxin Zhang
Jian-Dong Liu
FedML
OOD
AAML
35
10
0
03 Jul 2021
Adversarial Examples Make Strong Poisons
Adversarial Examples Make Strong Poisons
Liam H. Fowl
Micah Goldblum
Ping Yeh-Chiang
Jonas Geiping
Wojtek Czaja
Tom Goldstein
SILM
37
132
0
21 Jun 2021
Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks
  Trained from Scratch
Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from Scratch
Hossein Souri
Liam H. Fowl
Ramalingam Chellappa
Micah Goldblum
Tom Goldstein
SILM
31
124
0
16 Jun 2021
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks
Chulin Xie
Minghao Chen
Pin-Yu Chen
Bo Li
FedML
36
165
0
15 Jun 2021
Privacy Assessment of Federated Learning using Private Personalized
  Layers
Privacy Assessment of Federated Learning using Private Personalized Layers
T. Jourdan
A. Boutet
Carole Frindel
FedML
47
7
0
15 Jun 2021
Gradient Disaggregation: Breaking Privacy in Federated Learning by
  Reconstructing the User Participant Matrix
Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix
Maximilian Lam
Gu-Yeon Wei
David Brooks
Vijay Janapa Reddi
Michael Mitzenmacher
FedML
20
63
0
10 Jun 2021
Federated Neural Collaborative Filtering
Federated Neural Collaborative Filtering
V. Perifanis
P. Efraimidis
FedML
21
92
0
02 Jun 2021
RBNN: Memory-Efficient Reconfigurable Deep Binary Neural Network with IP
  Protection for Internet of Things
RBNN: Memory-Efficient Reconfigurable Deep Binary Neural Network with IP Protection for Internet of Things
Huming Qiu
Hua Ma
Zhi-Li Zhang
Yifeng Zheng
Anmin Fu
Pan Zhou
Yansong Gao
Derek Abbott
S. Al-Sarawi
MQ
24
9
0
09 May 2021
FedGL: Federated Graph Learning Framework with Global Self-Supervision
FedGL: Federated Graph Learning Framework with Global Self-Supervision
Chuan Chen
Weibo Hu
Ziyue Xu
Zibin Zheng
FedML
27
54
0
07 May 2021
Citadel: Protecting Data Privacy and Model Confidentiality for
  Collaborative Learning with SGX
Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning with SGX
Chengliang Zhang
Junzhe Xia
Baichen Yang
Huancheng Puyang
Wei Wang
Ruichuan Chen
Istemi Ekin Akkus
Paarijaat Aditya
Feng Yan
FedML
53
39
0
04 May 2021
Privacy-Preserving Federated Learning on Partitioned Attributes
Privacy-Preserving Federated Learning on Partitioned Attributes
Shuang Zhang
Liyao Xiang
Xi Yu
Pengzhi Chu
Yingqi Chen
Chen Cen
L. Wang
FedML
28
2
0
29 Apr 2021
From Distributed Machine Learning to Federated Learning: A Survey
From Distributed Machine Learning to Federated Learning: A Survey
Ji Liu
Jizhou Huang
Yang Zhou
Xuhong Li
Shilei Ji
Haoyi Xiong
Dejing Dou
FedML
OOD
56
244
0
29 Apr 2021
Turning Federated Learning Systems Into Covert Channels
Turning Federated Learning Systems Into Covert Channels
Gabriele Costa
Fabio Pinelli
S. Soderi
Gabriele Tolomei
FedML
37
10
0
21 Apr 2021
Robust Backdoor Attacks against Deep Neural Networks in Real Physical
  World
Robust Backdoor Attacks against Deep Neural Networks in Real Physical World
Mingfu Xue
Can He
Shichang Sun
Jian Wang
Weiqiang Liu
AAML
34
43
0
15 Apr 2021
Federated Learning with Taskonomy for Non-IID Data
Federated Learning with Taskonomy for Non-IID Data
Hadi Jamali Rad
Mohammad Abdizadeh
Anuj Singh
FedML
48
54
0
29 Mar 2021
Privacy and Trust Redefined in Federated Machine Learning
Privacy and Trust Redefined in Federated Machine Learning
Pavlos Papadopoulos
Will Abramson
A. Hall
Nikolaos Pitropakis
William J. Buchanan
33
42
0
29 Mar 2021
Black-box Detection of Backdoor Attacks with Limited Information and
  Data
Black-box Detection of Backdoor Attacks with Limited Information and Data
Yinpeng Dong
Xiao Yang
Zhijie Deng
Tianyu Pang
Zihao Xiao
Hang Su
Jun Zhu
AAML
21
113
0
24 Mar 2021
SoK: Privacy-Preserving Collaborative Tree-based Model Learning
SoK: Privacy-Preserving Collaborative Tree-based Model Learning
Sylvain Chatel
Apostolos Pyrgelis
J. Troncoso-Pastoriza
Jean-Pierre Hubaux
22
14
0
16 Mar 2021
EX-RAY: Distinguishing Injected Backdoor from Natural Features in Neural
  Networks by Examining Differential Feature Symmetry
EX-RAY: Distinguishing Injected Backdoor from Natural Features in Neural Networks by Examining Differential Feature Symmetry
Yingqi Liu
Guangyu Shen
Guanhong Tao
Zhenting Wang
Shiqing Ma
Xinming Zhang
AAML
40
8
0
16 Mar 2021
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