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2205.01992
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Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning
4 May 2022
Antonio Emanuele Cinà
Kathrin Grosse
Ambra Demontis
Sebastiano Vascon
Werner Zellinger
Bernhard A. Moser
Alina Oprea
Battista Biggio
Marcello Pelillo
Fabio Roli
AAML
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Papers citing
"Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning"
25 / 25 papers shown
Title
Artificial Intelligence health advice accuracy varies across languages and contexts
Prashant Garg
Thiemo Fetzer
56
0
0
25 Apr 2025
Statistically Testing Training Data for Unwanted Error Patterns using Rule-Oriented Regression
Stefan Rass
Martin Dallinger
54
0
0
24 Mar 2025
Position: A taxonomy for reporting and describing AI security incidents
L. Bieringer
Kevin Paeth
Andreas Wespi
Kathrin Grosse
Alexandre Alahi
Kathrin Grosse
78
0
0
19 Dec 2024
Human-inspired Perspectives: A Survey on AI Long-term Memory
Zihong He
Weizhe Lin
Hao Zheng
Fan Zhang
Matt Jones
Laurence Aitchison
X. Xu
Miao Liu
Per Ola Kristensson
Junxiao Shen
77
2
0
01 Nov 2024
Timber! Poisoning Decision Trees
Stefano Calzavara
Lorenzo Cazzaro
Massimo Vettori
AAML
30
0
0
01 Oct 2024
Machine Unlearning Fails to Remove Data Poisoning Attacks
Martin Pawelczyk
Jimmy Z. Di
Yiwei Lu
Gautam Kamath
Ayush Sekhari
Seth Neel
AAML
MU
62
8
0
25 Jun 2024
Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems
Guangjing Wang
Ce Zhou
Yuanda Wang
Bocheng Chen
Hanqing Guo
Qiben Yan
AAML
SILM
68
3
0
20 Nov 2023
Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training
Dario Lazzaro
Antonio Emanuele Cinà
Maura Pintor
Ambra Demontis
Battista Biggio
Fabio Roli
Marcello Pelillo
27
7
0
01 Jul 2023
On the Exploitability of Instruction Tuning
Manli Shu
Jiong Wang
Chen Zhu
Jonas Geiping
Chaowei Xiao
Tom Goldstein
SILM
36
91
0
28 Jun 2023
A Proxy Attack-Free Strategy for Practically Improving the Poisoning Efficiency in Backdoor Attacks
Ziqiang Li
Hong Sun
Pengfei Xia
Beihao Xia
Xue Rui
Wei Zhang
Qinglang Guo
Bin Li
AAML
32
8
0
14 Jun 2023
On the Limitations of Model Stealing with Uncertainty Quantification Models
David Pape
Sina Daubener
Thorsten Eisenhofer
Antonio Emanuele Cinà
Lea Schonherr
33
3
0
09 May 2023
Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks
Jimmy Z. Di
Jack Douglas
Jayadev Acharya
Gautam Kamath
Ayush Sekhari
MU
32
44
0
21 Dec 2022
Thinking Two Moves Ahead: Anticipating Other Users Improves Backdoor Attacks in Federated Learning
Yuxin Wen
Jonas Geiping
Liam H. Fowl
Hossein Souri
Ramalingam Chellappa
Micah Goldblum
Tom Goldstein
AAML
SILM
FedML
30
9
0
17 Oct 2022
On the Robustness of Random Forest Against Untargeted Data Poisoning: An Ensemble-Based Approach
M. Anisetti
C. Ardagna
Alessandro Balestrucci
Nicola Bena
Ernesto Damiani
C. Yeun
AAML
OOD
32
10
0
28 Sep 2022
Machine Learning Security in Industry: A Quantitative Survey
Kathrin Grosse
L. Bieringer
Tarek R. Besold
Battista Biggio
Katharina Krombholz
37
32
0
11 Jul 2022
On Collective Robustness of Bagging Against Data Poisoning
Ruoxin Chen
Zenan Li
Jie Li
Chentao Wu
Junchi Yan
56
23
0
26 May 2022
Indiscriminate Data Poisoning Attacks on Neural Networks
Yiwei Lu
Gautam Kamath
Yaoliang Yu
AAML
43
24
0
19 Apr 2022
Machine Learning Security against Data Poisoning: Are We There Yet?
Antonio Emanuele Cinà
Kathrin Grosse
Ambra Demontis
Battista Biggio
Fabio Roli
Marcello Pelillo
AAML
24
35
0
12 Apr 2022
Energy-Latency Attacks via Sponge Poisoning
Antonio Emanuele Cinà
Ambra Demontis
Battista Biggio
Fabio Roli
Marcello Pelillo
SILM
50
29
0
14 Mar 2022
Regularization Can Help Mitigate Poisoning Attacks... with the Right Hyperparameters
Javier Carnerero-Cano
Luis Muñoz-González
P. Spencer
Emil C. Lupu
AAML
36
10
0
23 May 2021
Mitigating backdoor attacks in LSTM-based Text Classification Systems by Backdoor Keyword Identification
Chuanshuai Chen
Jiazhu Dai
SILM
55
125
0
11 Jul 2020
Clean-Label Backdoor Attacks on Video Recognition Models
Shihao Zhao
Xingjun Ma
Xiang Zheng
James Bailey
Jingjing Chen
Yu-Gang Jiang
AAML
198
274
0
06 Mar 2020
SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems
Edward Chou
Florian Tramèr
Giancarlo Pellegrino
AAML
168
287
0
02 Dec 2018
Analyzing Federated Learning through an Adversarial Lens
A. Bhagoji
Supriyo Chakraborty
Prateek Mittal
S. Calo
FedML
191
1,032
0
29 Nov 2018
Bilevel Programming for Hyperparameter Optimization and Meta-Learning
Luca Franceschi
P. Frasconi
Saverio Salzo
Riccardo Grazzi
Massimiliano Pontil
110
717
0
13 Jun 2018
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