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Venomancer: Towards Imperceptible and Target-on-Demand Backdoor Attacks
  in Federated Learning
v1v2 (latest)

Venomancer: Towards Imperceptible and Target-on-Demand Backdoor Attacks in Federated Learning

3 July 2024
Son Nguyen
Thinh Nguyen
Khoa D. Doan
Kok-Seng Wong
    FedMLAAML
ArXiv (abs)PDFHTMLGithub (4★)

Papers citing "Venomancer: Towards Imperceptible and Target-on-Demand Backdoor Attacks in Federated Learning"

18 / 18 papers shown
Title
Batch Label Inference and Replacement Attacks in Black-Boxed Vertical
  Federated Learning
Batch Label Inference and Replacement Attacks in Black-Boxed Vertical Federated Learning
Yang Liu
Tianyuan Zou
Yan Kang
Wenhan Liu
Yuanqin He
Zhi-qian Yi
Qian Yang
FedMLAAML
109
20
0
10 Dec 2021
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
Hongyi Wang
Kartik K. Sreenivasan
Shashank Rajput
Harit Vishwakarma
Saurabh Agarwal
Jy-yong Sohn
Kangwook Lee
Dimitris Papailiopoulos
FedML
87
611
0
09 Jul 2020
Agent57: Outperforming the Atari Human Benchmark
Agent57: Outperforming the Atari Human Benchmark
Adria Puigdomenech Badia
Bilal Piot
Steven Kapturowski
Pablo Sprechmann
Alex Vitvitskyi
Daniel Guo
Charles Blundell
OffRL
91
521
0
30 Mar 2020
Can You Really Backdoor Federated Learning?
Can You Really Backdoor Federated Learning?
Ziteng Sun
Peter Kairouz
A. Suresh
H. B. McMahan
FedML
85
579
0
18 Nov 2019
Federated Learning with Differential Privacy: Algorithms and Performance
  Analysis
Federated Learning with Differential Privacy: Algorithms and Performance Analysis
Kang Wei
Jun Li
Ming Ding
Chuan Ma
Heng Yang
Farokhi Farhad
Shi Jin
Tony Q.S. Quek
H. Vincent Poor
FedML
129
1,628
0
01 Nov 2019
Federated Learning for Keyword Spotting
Federated Learning for Keyword Spotting
David Leroy
A. Coucke
Thibaut Lavril
Thibault Gisselbrecht
Joseph Dureau
FedML
88
287
0
09 Oct 2018
The History Began from AlexNet: A Comprehensive Survey on Deep Learning
  Approaches
The History Began from AlexNet: A Comprehensive Survey on Deep Learning Approaches
Md. Zahangir Alom
T. Taha
C. Yakopcic
Stefan Westberg
P. Sidike
Mst Shamima Nasrin
B. Van Essen
A. Awwal
V. Asari
VLM
97
882
0
03 Mar 2018
Towards Imperceptible and Robust Adversarial Example Attacks against
  Neural Networks
Towards Imperceptible and Robust Adversarial Example Attacks against Neural Networks
Bo Luo
Yannan Liu
Lingxiao Wei
Q. Xu
AAML
53
142
0
15 Jan 2018
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning
Xinyun Chen
Chang-rui Liu
Yue Liu
Kimberly Lu
Basel Alomair
AAMLSILM
146
1,854
0
15 Dec 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning
  Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
285
8,928
0
25 Aug 2017
Federated Learning: Strategies for Improving Communication Efficiency
Federated Learning: Strategies for Improving Communication Efficiency
Jakub Konecný
H. B. McMahan
Felix X. Yu
Peter Richtárik
A. Suresh
Dave Bacon
FedML
312
4,657
0
18 Oct 2016
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based
  Localization
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Ramprasaath R. Selvaraju
Michael Cogswell
Abhishek Das
Ramakrishna Vedantam
Devi Parikh
Dhruv Batra
FAtt
335
20,110
0
07 Oct 2016
Deep Learning with Differential Privacy
Deep Learning with Differential Privacy
Martín Abadi
Andy Chu
Ian Goodfellow
H. B. McMahan
Ilya Mironov
Kunal Talwar
Li Zhang
FedMLSyDa
216
6,172
0
01 Jul 2016
Communication-Efficient Learning of Deep Networks from Decentralized
  Data
Communication-Efficient Learning of Deep Networks from Decentralized Data
H. B. McMahan
Eider Moore
Daniel Ramage
S. Hampson
Blaise Agüera y Arcas
FedML
408
17,615
0
17 Feb 2016
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg3DV
1.9K
77,441
0
18 May 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
2.1K
150,364
0
22 Dec 2014
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAMLGAN
282
19,129
0
20 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAttMDE
1.7K
100,529
0
04 Sep 2014
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