Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
1812.04293
Cited By
v1
v2
v3
v4 (latest)
On the Security of Randomized Defenses Against Adversarial Samples
11 December 2018
K. Sharad
G. Marson
H. Truong
Ghassan O. Karame
AAML
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"On the Security of Randomized Defenses Against Adversarial Samples"
15 / 15 papers shown
Title
On Evaluating Adversarial Robustness
Nicholas Carlini
Anish Athalye
Nicolas Papernot
Wieland Brendel
Jonas Rauber
Dimitris Tsipras
Ian Goodfellow
Aleksander Madry
Alexey Kurakin
ELM
AAML
89
901
0
18 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing
Jeremy M. Cohen
Elan Rosenfeld
J. Zico Kolter
AAML
152
2,044
0
08 Feb 2019
A Simple Explanation for the Existence of Adversarial Examples with Small Hamming Distance
A. Shamir
Itay Safran
Eyal Ronen
O. Dunkelman
GAN
AAML
37
94
0
30 Jan 2019
Are adversarial examples inevitable?
Ali Shafahi
Wenjie Huang
Christoph Studer
Soheil Feizi
Tom Goldstein
SILM
72
283
0
06 Sep 2018
Adversarial examples from computational constraints
Sébastien Bubeck
Eric Price
Ilya P. Razenshteyn
AAML
119
233
0
25 May 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye
Nicholas Carlini
D. Wagner
AAML
230
3,186
0
01 Feb 2018
Mitigating Adversarial Effects Through Randomization
Cihang Xie
Jianyu Wang
Zhishuai Zhang
Zhou Ren
Alan Yuille
AAML
113
1,059
0
06 Nov 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
310
12,069
0
19 Jun 2017
Extending Defensive Distillation
Nicolas Papernot
Patrick McDaniel
AAML
64
119
0
15 May 2017
Detecting Adversarial Samples from Artifacts
Reuben Feinman
Ryan R. Curtin
S. Shintre
Andrew B. Gardner
AAML
93
893
0
01 Mar 2017
On the (Statistical) Detection of Adversarial Examples
Kathrin Grosse
Praveen Manoharan
Nicolas Papernot
Michael Backes
Patrick McDaniel
AAML
76
714
0
21 Feb 2017
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
472
3,144
0
04 Nov 2016
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
543
5,897
0
08 Jul 2016
Adversarial Perturbations Against Deep Neural Networks for Malware Classification
Kathrin Grosse
Nicolas Papernot
Praveen Manoharan
Michael Backes
Patrick McDaniel
AAML
64
418
0
14 Jun 2016
DeepFool: a simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
P. Frossard
AAML
151
4,897
0
14 Nov 2015
1