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On the (Statistical) Detection of Adversarial Examples

On the (Statistical) Detection of Adversarial Examples

21 February 2017
Kathrin Grosse
Praveen Manoharan
Nicolas Papernot
Michael Backes
Patrick McDaniel
    AAML
ArXivPDFHTML

Papers citing "On the (Statistical) Detection of Adversarial Examples"

22 / 122 papers shown
Title
Defending Against Adversarial Attacks by Leveraging an Entire GAN
Defending Against Adversarial Attacks by Leveraging an Entire GAN
G. Santhanam
Paulina Grnarova
AAML
16
40
0
27 May 2018
Detecting Adversarial Samples for Deep Neural Networks through Mutation
  Testing
Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing
Jingyi Wang
Jun Sun
Peixin Zhang
Xinyu Wang
AAML
21
41
0
14 May 2018
Towards Dependable Deep Convolutional Neural Networks (CNNs) with
  Out-distribution Learning
Towards Dependable Deep Convolutional Neural Networks (CNNs) with Out-distribution Learning
Mahdieh Abbasi
Arezoo Rajabi
Christian Gagné
R. Bobba
OODD
30
6
0
24 Apr 2018
DeepSigns: A Generic Watermarking Framework for IP Protection of Deep
  Learning Models
DeepSigns: A Generic Watermarking Framework for IP Protection of Deep Learning Models
B. Rouhani
Huili Chen
F. Koushanfar
40
48
0
02 Apr 2018
Defending against Adversarial Attack towards Deep Neural Networks via
  Collaborative Multi-task Training
Defending against Adversarial Attack towards Deep Neural Networks via Collaborative Multi-task Training
Derui Wang
Chaoran Li
S. Wen
Surya Nepal
Yang Xiang
AAML
38
29
0
14 Mar 2018
On the Suitability of $L_p$-norms for Creating and Preventing
  Adversarial Examples
On the Suitability of LpL_pLp​-norms for Creating and Preventing Adversarial Examples
Mahmood Sharif
Lujo Bauer
Michael K. Reiter
AAML
21
138
0
27 Feb 2018
Unravelling Robustness of Deep Learning based Face Recognition Against
  Adversarial Attacks
Unravelling Robustness of Deep Learning based Face Recognition Against Adversarial Attacks
Gaurav Goswami
Nalini Ratha
Akshay Agarwal
Richa Singh
Mayank Vatsa
AAML
18
165
0
22 Feb 2018
Generalizable Adversarial Examples Detection Based on Bi-model Decision
  Mismatch
Generalizable Adversarial Examples Detection Based on Bi-model Decision Mismatch
João Monteiro
Isabela Albuquerque
Zahid Akhtar
T. Falk
AAML
38
29
0
21 Feb 2018
On Lyapunov exponents and adversarial perturbation
On Lyapunov exponents and adversarial perturbation
Vinay Uday Prabhu
Nishant Desai
John Whaley
AAML
20
4
0
20 Feb 2018
Characterizing Adversarial Subspaces Using Local Intrinsic
  Dimensionality
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality
Xingjun Ma
Bo-wen Li
Yisen Wang
S. Erfani
S. Wijewickrema
Grant Schoenebeck
D. Song
Michael E. Houle
James Bailey
AAML
34
728
0
08 Jan 2018
A General Framework for Adversarial Examples with Objectives
A General Framework for Adversarial Examples with Objectives
Mahmood Sharif
Sruti Bhagavatula
Lujo Bauer
Michael K. Reiter
AAML
GAN
13
191
0
31 Dec 2017
The Robust Manifold Defense: Adversarial Training using Generative
  Models
The Robust Manifold Defense: Adversarial Training using Generative Models
A. Jalal
Andrew Ilyas
C. Daskalakis
A. Dimakis
AAML
31
174
0
26 Dec 2017
Improving Network Robustness against Adversarial Attacks with Compact
  Convolution
Improving Network Robustness against Adversarial Attacks with Compact Convolution
Rajeev Ranjan
S. Sankaranarayanan
Carlos D. Castillo
Rama Chellappa
AAML
21
14
0
03 Dec 2017
Towards Robust Neural Networks via Random Self-ensemble
Towards Robust Neural Networks via Random Self-ensemble
Xuanqing Liu
Minhao Cheng
Huan Zhang
Cho-Jui Hsieh
FedML
AAML
55
418
0
02 Dec 2017
MARGIN: Uncovering Deep Neural Networks using Graph Signal Analysis
MARGIN: Uncovering Deep Neural Networks using Graph Signal Analysis
Rushil Anirudh
Jayaraman J. Thiagarajan
R. Sridhar
T. Bremer
FAtt
AAML
23
12
0
15 Nov 2017
Detecting Adversarial Attacks on Neural Network Policies with Visual
  Foresight
Detecting Adversarial Attacks on Neural Network Policies with Visual Foresight
Yen-Chen Lin
Ming Liu
Min Sun
Jia-Bin Huang
AAML
29
48
0
02 Oct 2017
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial
  Examples
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples
Pin-Yu Chen
Yash Sharma
Huan Zhang
Jinfeng Yi
Cho-Jui Hsieh
AAML
24
637
0
13 Sep 2017
Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong
Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong
Warren He
James Wei
Xinyun Chen
Nicholas Carlini
D. Song
AAML
43
242
0
15 Jun 2017
MagNet: a Two-Pronged Defense against Adversarial Examples
MagNet: a Two-Pronged Defense against Adversarial Examples
Dongyu Meng
Hao Chen
AAML
13
1,196
0
25 May 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection
  Methods
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods
Nicholas Carlini
D. Wagner
AAML
61
1,842
0
20 May 2017
Extending Defensive Distillation
Extending Defensive Distillation
Nicolas Papernot
Patrick McDaniel
AAML
32
118
0
15 May 2017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural
  Networks
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks
Weilin Xu
David Evans
Yanjun Qi
AAML
25
1,233
0
04 Apr 2017
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