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Wild Patterns Reloaded: A Survey of Machine Learning Security against
  Training Data Poisoning

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
ArXivPDFHTML

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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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?
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
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
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
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
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
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
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
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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