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Contamination Attacks and Mitigation in Multi-Party Machine Learning

Contamination Attacks and Mitigation in Multi-Party Machine Learning

8 January 2019
Jamie Hayes
O. Ohrimenko
    AAML
    FedML
ArXivPDFHTML

Papers citing "Contamination Attacks and Mitigation in Multi-Party Machine Learning"

13 / 13 papers shown
Title
Logit Poisoning Attack in Distillation-based Federated Learning and its
  Countermeasures
Logit Poisoning Attack in Distillation-based Federated Learning and its Countermeasures
Yonghao Yu
Shunan Zhu
Jinglu Hu
AAML
FedML
35
0
0
31 Jan 2024
Digital Privacy Under Attack: Challenges and Enablers
Digital Privacy Under Attack: Challenges and Enablers
Baobao Song
Mengyue Deng
Shiva Raj Pokhrel
Qiujun Lan
R. Doss
Gang Li
AAML
39
3
0
18 Feb 2023
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
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
36
7
0
28 Jan 2022
Hiding Behind Backdoors: Self-Obfuscation Against Generative Models
Hiding Behind Backdoors: Self-Obfuscation Against Generative Models
Siddhartha Datta
N. Shadbolt
SILM
AAML
AI4CE
25
2
0
24 Jan 2022
Incentivizing Collaboration in Machine Learning via Synthetic Data
  Rewards
Incentivizing Collaboration in Machine Learning via Synthetic Data Rewards
Sebastian Shenghong Tay
Xinyi Xu
Chuan-Sheng Foo
Bryan Kian Hsiang Low
SyDa
24
32
0
17 Dec 2021
Robustness Threats of Differential Privacy
Robustness Threats of Differential Privacy
Nurislam Tursynbek
Aleksandr Petiushko
Ivan Oseledets
AAML
30
14
0
14 Dec 2020
From Distributed Machine Learning To Federated Learning: In The View Of
  Data Privacy And Security
From Distributed Machine Learning To Federated Learning: In The View Of Data Privacy And Security
Sheng Shen
Tianqing Zhu
Di Wu
Wei Wang
Wanlei Zhou
FedML
OOD
23
77
0
19 Oct 2020
On Second-Order Group Influence Functions for Black-Box Predictions
On Second-Order Group Influence Functions for Black-Box Predictions
S. Basu
Xuchen You
S. Feizi
TDI
22
68
0
01 Nov 2019
Privacy Risks of Securing Machine Learning Models against Adversarial
  Examples
Privacy Risks of Securing Machine Learning Models against Adversarial Examples
Liwei Song
Reza Shokri
Prateek Mittal
SILM
MIACV
AAML
6
235
0
24 May 2019
Prochlo: Strong Privacy for Analytics in the Crowd
Prochlo: Strong Privacy for Analytics in the Crowd
Andrea Bittau
Ulfar Erlingsson
Petros Maniatis
Ilya Mironov
A. Raghunathan
David Lie
Mitch Rudominer
Ushasree Kode
J. Tinnés
B. Seefeld
91
278
0
02 Oct 2017
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
317
5,847
0
08 Jul 2016
Convolutional Neural Networks for Sentence Classification
Convolutional Neural Networks for Sentence Classification
Yoon Kim
AILaw
VLM
291
13,373
0
25 Aug 2014
1