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Adversarial Scratches: Deployable Attacks to CNN Classifiers

Adversarial Scratches: Deployable Attacks to CNN Classifiers

20 April 2022
Loris Giulivi
Malhar Jere
Loris Rossi
F. Koushanfar
Gabriela F. Cretu-Ciocarlie
Briland Hitaj
Giacomo Boracchi
    AAML
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Papers citing "Adversarial Scratches: Deployable Attacks to CNN Classifiers"

21 / 21 papers shown
Title
A black-box adversarial attack for poisoning clustering
A black-box adversarial attack for poisoning clustering
Antonio Emanuele Cinà
Alessandro Torcinovich
Marcello Pelillo
AAML
39
40
0
09 Sep 2020
Security and Machine Learning in the Real World
Security and Machine Learning in the Real World
Ivan Evtimov
Weidong Cui
Ece Kamar
Emre Kıcıman
Tadayoshi Kohno
Jingkai Li
AAML
34
15
0
13 Jul 2020
Sparse-RS: a versatile framework for query-efficient sparse black-box
  adversarial attacks
Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks
Francesco Croce
Maksym Andriushchenko
Naman D. Singh
Nicolas Flammarion
Matthias Hein
71
101
0
23 Jun 2020
Adversarial Training against Location-Optimized Adversarial Patches
Adversarial Training against Location-Optimized Adversarial Patches
Sukrut Rao
David Stutz
Bernt Schiele
AAML
46
92
0
05 May 2020
A Black-box Adversarial Attack Strategy with Adjustable Sparsity and
  Generalizability for Deep Image Classifiers
A Black-box Adversarial Attack Strategy with Adjustable Sparsity and Generalizability for Deep Image Classifiers
Arka Ghosh
S. S. Mullick
Shounak Datta
Swagatam Das
R. Mallipeddi
A. Das
AAML
38
37
0
24 Apr 2020
PatchAttack: A Black-box Texture-based Attack with Reinforcement
  Learning
PatchAttack: A Black-box Texture-based Attack with Reinforcement Learning
Chenglin Yang
Adam Kortylewski
Cihang Xie
Yinzhi Cao
Alan Yuille
AAML
68
109
0
12 Apr 2020
Sparse and Imperceivable Adversarial Attacks
Sparse and Imperceivable Adversarial Attacks
Francesco Croce
Matthias Hein
AAML
94
199
0
11 Sep 2019
Simple Black-box Adversarial Attacks
Simple Black-box Adversarial Attacks
Chuan Guo
Jacob R. Gardner
Yurong You
A. Wilson
Kilian Q. Weinberger
AAML
60
578
0
17 May 2019
Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial
  Optimization
Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial Optimization
Seungyong Moon
Gaon An
Hyun Oh Song
AAML
MLAU
47
134
0
16 May 2019
SparseFool: a few pixels make a big difference
SparseFool: a few pixels make a big difference
Apostolos Modas
Seyed-Mohsen Moosavi-Dezfooli
P. Frossard
AAML
53
199
0
06 Nov 2018
Deep learning at the shallow end: Malware classification for non-domain
  experts
Deep learning at the shallow end: Malware classification for non-domain experts
Quan Le
Oisín Boydell
Brian Mac Namee
Mark Scanlon
102
173
0
22 Jul 2018
Black-box Adversarial Attacks with Limited Queries and Information
Black-box Adversarial Attacks with Limited Queries and Information
Andrew Ilyas
Logan Engstrom
Anish Athalye
Jessy Lin
MLAU
AAML
163
1,200
0
23 Apr 2018
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box
  Machine Learning Models
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models
Wieland Brendel
Jonas Rauber
Matthias Bethge
AAML
65
1,345
0
12 Dec 2017
Mastering Chess and Shogi by Self-Play with a General Reinforcement
  Learning Algorithm
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
David Silver
Thomas Hubert
Julian Schrittwieser
Ioannis Antonoglou
Matthew Lai
...
D. Kumaran
T. Graepel
Timothy Lillicrap
Karen Simonyan
Demis Hassabis
141
1,771
0
05 Dec 2017
Evasion Attacks against Machine Learning at Test Time
Evasion Attacks against Machine Learning at Test Time
Battista Biggio
Igino Corona
Davide Maiorca
B. Nelson
Nedim Srndic
Pavel Laskov
Giorgio Giacinto
Fabio Roli
AAML
157
2,151
0
21 Aug 2017
Rethinking the Inception Architecture for Computer Vision
Rethinking the Inception Architecture for Computer Vision
Christian Szegedy
Vincent Vanhoucke
Sergey Ioffe
Jonathon Shlens
Z. Wojna
3DV
BDL
883
27,358
0
02 Dec 2015
The Limitations of Deep Learning in Adversarial Settings
The Limitations of Deep Learning in Adversarial Settings
Nicolas Papernot
Patrick McDaniel
S. Jha
Matt Fredrikson
Z. Berkay Celik
A. Swami
AAML
105
3,960
0
24 Nov 2015
Deep Speech: Scaling up end-to-end speech recognition
Deep Speech: Scaling up end-to-end speech recognition
Awni Y. Hannun
Carl Case
Jared Casper
Bryan Catanzaro
G. Diamos
...
R. Prenger
S. Satheesh
Shubho Sengupta
Adam Coates
A. Ng
180
2,124
0
17 Dec 2014
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
1.7K
39,525
0
01 Sep 2014
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
270
14,918
1
21 Dec 2013
Poisoning Attacks against Support Vector Machines
Poisoning Attacks against Support Vector Machines
Battista Biggio
B. Nelson
Pavel Laskov
AAML
109
1,589
0
27 Jun 2012
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