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Explaining and Harnessing Adversarial Examples
v1v2v3 (latest)

Explaining and Harnessing Adversarial Examples

20 December 2014
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
    AAMLGAN
ArXiv (abs)PDFHTML

Papers citing "Explaining and Harnessing Adversarial Examples"

50 / 8,379 papers shown
Title
Good-looking but Lacking Faithfulness: Understanding Local Explanation
  Methods through Trend-based Testing
Good-looking but Lacking Faithfulness: Understanding Local Explanation Methods through Trend-based Testing
Jinwen He
Kai Chen
Guozhu Meng
Jiangshan Zhang
Congyi Li
FAttAAML
78
3
0
09 Sep 2023
Compact: Approximating Complex Activation Functions for Secure
  Computation
Compact: Approximating Complex Activation Functions for Secure Computation
Mazharul Islam
Sunpreet S. Arora
Rahul Chatterjee
Peter Rindal
Maliheh Shirvanian
85
4
0
09 Sep 2023
Exploring Robust Features for Improving Adversarial Robustness
Exploring Robust Features for Improving Adversarial Robustness
Hong Wang
Yuefan Deng
Shinjae Yoo
Yuewei Lin
AAML
100
4
0
09 Sep 2023
Fuzzy Fingerprinting Transformer Language-Models for Emotion Recognition
  in Conversations
Fuzzy Fingerprinting Transformer Language-Models for Emotion Recognition in Conversations
Patrícia Pereira
Rui Ribeiro
Helena Moniz
Luísa Coheur
Joao Paulo Carvalho
60
6
0
08 Sep 2023
FIVA: Facial Image and Video Anonymization and Anonymization Defense
FIVA: Facial Image and Video Anonymization and Anonymization Defense
Felix Rosberg
E. Aksoy
Cristofer Englund
F. Alonso-Fernandez
AAMLPICV
80
5
0
08 Sep 2023
Adversarial attacks on hybrid classical-quantum Deep Learning models for
  Histopathological Cancer Detection
Adversarial attacks on hybrid classical-quantum Deep Learning models for Histopathological Cancer Detection
Biswaraj Baral
Reek Majumdar
Bhavika Bhalgamiya
Taposh Dutta Roy
MedImAAML
118
1
0
08 Sep 2023
DiffDefense: Defending against Adversarial Attacks via Diffusion Models
DiffDefense: Defending against Adversarial Attacks via Diffusion Models
Hondamunige Prasanna Silva
Lorenzo Seidenari
A. Bimbo
DiffM
59
7
0
07 Sep 2023
How adversarial attacks can disrupt seemingly stable accurate
  classifiers
How adversarial attacks can disrupt seemingly stable accurate classifiers
Oliver J. Sutton
Qinghua Zhou
I. Tyukin
Alexander N. Gorban
Alexander Bastounis
D. Higham
AAML
79
1
0
07 Sep 2023
Your Battery Is a Blast! Safeguarding Against Counterfeit Batteries with
  Authentication
Your Battery Is a Blast! Safeguarding Against Counterfeit Batteries with Authentication
Francesco Marchiori
Mauro Conti
78
7
0
07 Sep 2023
SWAP: Exploiting Second-Ranked Logits for Adversarial Attacks on Time
  Series
SWAP: Exploiting Second-Ranked Logits for Adversarial Attacks on Time Series
Chang George Dong
Liangwei Nathan Zheng
Weitong Chen
Wei Emma Zhang
Lin Yue
AAML
59
7
0
06 Sep 2023
Certifying LLM Safety against Adversarial Prompting
Certifying LLM Safety against Adversarial Prompting
Aounon Kumar
Chirag Agarwal
Suraj Srinivas
Aaron Jiaxun Li
Soheil Feizi
Himabindu Lakkaraju
AAML
157
197
0
06 Sep 2023
Adaptive Adversarial Training Does Not Increase Recourse Costs
Adaptive Adversarial Training Does Not Increase Recourse Costs
Ian Hardy
Jayanth Yetukuri
Yang Liu
AAML
59
1
0
05 Sep 2023
Towards User Guided Actionable Recourse
Towards User Guided Actionable Recourse
Jayanth Yetukuri
Ian Hardy
Yang Liu
50
2
0
05 Sep 2023
The Adversarial Implications of Variable-Time Inference
The Adversarial Implications of Variable-Time Inference
Dudi Biton
Aditi Misra
Efrat Levy
J. Kotak
Ron Bitton
R. Schuster
Nicolas Papernot
Yuval Elovici
Ben Nassi
AAML
37
0
0
05 Sep 2023
Natural Example-Based Explainability: a Survey
Natural Example-Based Explainability: a Survey
Antonin Poché
Lucas Hervier
M. Bakkay
XAI
66
13
0
05 Sep 2023
Hindering Adversarial Attacks with Multiple Encrypted Patch Embeddings
Hindering Adversarial Attacks with Multiple Encrypted Patch Embeddings
AprilPyone Maungmaung
Isao Echizen
Hitoshi Kiya
AAML
64
2
0
04 Sep 2023
On the use of Mahalanobis distance for out-of-distribution detection
  with neural networks for medical imaging
On the use of Mahalanobis distance for out-of-distribution detection with neural networks for medical imaging
Harry Anthony
Konstantinos Kamnitsas
89
12
0
04 Sep 2023
Toward Defensive Letter Design
Toward Defensive Letter Design
Rentaro Kataoka
Akisato Kimura
Seiichi Uchida
AAML
41
0
0
04 Sep 2023
Open Sesame! Universal Black Box Jailbreaking of Large Language Models
Open Sesame! Universal Black Box Jailbreaking of Large Language Models
Raz Lapid
Ron Langberg
Moshe Sipper
AAML
135
112
0
04 Sep 2023
SemProtector: A Unified Framework for Semantic Protection in Deep
  Learning-based Semantic Communication Systems
SemProtector: A Unified Framework for Semantic Protection in Deep Learning-based Semantic Communication Systems
Xinghan Liu
Gu Nan
Qimei Cui
Zeju Li
Peiyuan Liu
Zebin Xing
Hanqing Mu
Xiaofeng Tao
Tony Q. S. Quek
AAML
60
16
0
04 Sep 2023
Robust and Efficient Interference Neural Networks for Defending Against
  Adversarial Attacks in ImageNet
Robust and Efficient Interference Neural Networks for Defending Against Adversarial Attacks in ImageNet
Yunuo Xiong
Shujuan Liu
H. Xiong
AAML
39
0
0
03 Sep 2023
AdvMono3D: Advanced Monocular 3D Object Detection with Depth-Aware
  Robust Adversarial Training
AdvMono3D: Advanced Monocular 3D Object Detection with Depth-Aware Robust Adversarial Training
Xingyuan Li
Jinyuan Liu
Long Ma
Xin-Yue Fan
Risheng Liu
AAML
95
3
0
03 Sep 2023
Turn Fake into Real: Adversarial Head Turn Attacks Against Deepfake
  Detection
Turn Fake into Real: Adversarial Head Turn Attacks Against Deepfake Detection
Weijie Wang
Zhengyu Zhao
N. Sebe
Bruno Lepri
AAML
83
2
0
03 Sep 2023
Robust Adversarial Defense by Tensor Factorization
Robust Adversarial Defense by Tensor Factorization
Manish Bhattarai
M. C. Kaymak
Ryan Barron
Ben Nebgen
Kim Ø. Rasmussen
Boian Alexandrov
AAML
65
2
0
03 Sep 2023
Online Adaptive Mahalanobis Distance Estimation
Online Adaptive Mahalanobis Distance Estimation
Lianke Qin
Aravind Reddy
Zhao Song
78
1
0
02 Sep 2023
AdLER: Adversarial Training with Label Error Rectification for One-Shot
  Medical Image Segmentation
AdLER: Adversarial Training with Label Error Rectification for One-Shot Medical Image Segmentation
Xiangyu Zhao
Sheng Wang
Zhiyun Song
Zhenrong Shen
Linlin Yao
Haolei Yuan
Qian Wang
Lichi Zhang
78
1
0
02 Sep 2023
Timbre-reserved Adversarial Attack in Speaker Identification
Timbre-reserved Adversarial Attack in Speaker Identification
Qing Wang
Jixun Yao
Li Zhang
Pengcheng Guo
Linfu Xie
AAML
81
4
0
02 Sep 2023
Towards Certified Probabilistic Robustness with High Accuracy
Towards Certified Probabilistic Robustness with High Accuracy
Ruihan Zhang
Peixin Zhang
Jun Sun
AAML
70
0
0
02 Sep 2023
Non-Asymptotic Bounds for Adversarial Excess Risk under Misspecified
  Models
Non-Asymptotic Bounds for Adversarial Excess Risk under Misspecified Models
Changyu Liu
Yuling Jiao
Junhui Wang
Jian Huang
AAML
45
2
0
02 Sep 2023
Baseline Defenses for Adversarial Attacks Against Aligned Language
  Models
Baseline Defenses for Adversarial Attacks Against Aligned Language Models
Neel Jain
Avi Schwarzschild
Yuxin Wen
Gowthami Somepalli
John Kirchenbauer
Ping Yeh-Chiang
Micah Goldblum
Aniruddha Saha
Jonas Geiping
Tom Goldstein
AAML
194
410
0
01 Sep 2023
Image Hijacks: Adversarial Images can Control Generative Models at
  Runtime
Image Hijacks: Adversarial Images can Control Generative Models at Runtime
Luke Bailey
Euan Ong
Stuart J. Russell
Scott Emmons
VLMMLLM
108
89
0
01 Sep 2023
Adversarial Finetuning with Latent Representation Constraint to Mitigate
  Accuracy-Robustness Tradeoff
Adversarial Finetuning with Latent Representation Constraint to Mitigate Accuracy-Robustness Tradeoff
Satoshi Suzuki
Shin'ya Yamaguchi
Shoichiro Takeda
Sekitoshi Kanai
Naoki Makishima
Atsushi Ando
Ryo Masumura
AAML
99
5
0
31 Aug 2023
Ten Years of Generative Adversarial Nets (GANs): A survey of the
  state-of-the-art
Ten Years of Generative Adversarial Nets (GANs): A survey of the state-of-the-art
Tanujit Chakraborty
Ujjwal Reddy K S
Shraddha M. Naik
Madhurima Panja
B. Manvitha
117
75
0
30 Aug 2023
Robust Principles: Architectural Design Principles for Adversarially
  Robust CNNs
Robust Principles: Architectural Design Principles for Adversarially Robust CNNs
Sheng-Hsuan Peng
Weilin Xu
Cory Cornelius
Matthew Hull
Kevin Wenliang Li
Rahul Duggal
Mansi Phute
Jason Martin
Duen Horng Chau
AAML
78
49
0
30 Aug 2023
Vulnerability of Machine Learning Approaches Applied in IoT-based Smart
  Grid: A Review
Vulnerability of Machine Learning Approaches Applied in IoT-based Smart Grid: A Review
Zhenyong Zhang
Mengxiang Liu
Mingyang Sun
Ruilong Deng
Peng Cheng
Dusit Niyato
Mo-Yuen Chow
Jiming Chen
115
47
0
30 Aug 2023
Intriguing Properties of Diffusion Models: An Empirical Study of the
  Natural Attack Capability in Text-to-Image Generative Models
Intriguing Properties of Diffusion Models: An Empirical Study of the Natural Attack Capability in Text-to-Image Generative Models
Takami Sato
Justin Yue
Nanze Chen
Ningfei Wang
Qi Alfred Chen
DiffM
74
3
0
30 Aug 2023
MDTD: A Multi Domain Trojan Detector for Deep Neural Networks
MDTD: A Multi Domain Trojan Detector for Deep Neural Networks
Arezoo Rajabi
Surudhi Asokraj
Feng-Shr Jiang
Luyao Niu
Bhaskar Ramasubramanian
J. Ritcey
Radha Poovendran
AAML
63
1
0
30 Aug 2023
Adaptive Attack Detection in Text Classification: Leveraging Space
  Exploration Features for Text Sentiment Classification
Adaptive Attack Detection in Text Classification: Leveraging Space Exploration Features for Text Sentiment Classification
Atefeh Mahdavi
Neda Keivandarian
Marco Carvalho
AAML
20
0
0
29 Aug 2023
Everything Perturbed All at Once: Enabling Differentiable Graph Attacks
Everything Perturbed All at Once: Enabling Differentiable Graph Attacks
Haoran Liu
Bokun Wang
Jianling Wang
Xiangjue Dong
Tianbao Yang
James Caverlee
AAML
107
3
0
29 Aug 2023
3D Adversarial Augmentations for Robust Out-of-Domain Predictions
3D Adversarial Augmentations for Robust Out-of-Domain Predictions
Alexander Lehner
Stefano Gasperini
Alvaro Marcos-Ramiro
Michael Schmidt
Nassir Navab
Benjamin Busam
F. Tombari
3DPC
91
8
0
29 Aug 2023
Imperceptible Adversarial Attack on Deep Neural Networks from Image
  Boundary
Imperceptible Adversarial Attack on Deep Neural Networks from Image Boundary
Fahad Alrasheedi
Agnibh Dasgupta
AAML
77
2
0
29 Aug 2023
Can We Rely on AI?
Can We Rely on AI?
D. Higham
AAML
65
0
0
29 Aug 2023
Advancing Adversarial Robustness Through Adversarial Logit Update
Advancing Adversarial Robustness Through Adversarial Logit Update
Hao Xuan
Peican Zhu
Xingyu Li
AAML
85
0
0
29 Aug 2023
OEBench: Investigating Open Environment Challenges in Real-World
  Relational Data Streams
OEBench: Investigating Open Environment Challenges in Real-World Relational Data Streams
Yiqun Diao
Yutong Yang
Yue Liu
Bin He
Mian Lu
85
3
0
29 Aug 2023
Is it an i or an l: Test-time Adaptation of Text Line Recognition Models
Is it an i or an l: Test-time Adaptation of Text Line Recognition Models
Debapriya Tula
S. Paul
Gagan Madan
P. Garst
R. Ingle
Gaurav Aggarwal
VLM
88
1
0
29 Aug 2023
Adversarial Attacks on Foundational Vision Models
Adversarial Attacks on Foundational Vision Models
Nathan Inkawhich
Gwendolyn McDonald
R. Luley
VLM
73
13
0
28 Aug 2023
The Promise and Peril of Artificial Intelligence -- Violet Teaming
  Offers a Balanced Path Forward
The Promise and Peril of Artificial Intelligence -- Violet Teaming Offers a Balanced Path Forward
A. Titus
Adam Russell
96
1
0
28 Aug 2023
Detecting Language Model Attacks with Perplexity
Detecting Language Model Attacks with Perplexity
Gabriel Alon
Michael Kamfonas
AAML
174
229
0
27 Aug 2023
The inverse problem for neural networks
The inverse problem for neural networks
M. Forets
Christian Schilling
81
0
0
27 Aug 2023
Adversarial Fine-Tuning of Language Models: An Iterative Optimisation
  Approach for the Generation and Detection of Problematic Content
Adversarial Fine-Tuning of Language Models: An Iterative Optimisation Approach for the Generation and Detection of Problematic Content
Charles OÑeill
Jack Miller
I. Ciucă
Y. Ting 丁
Thang Bui
70
5
0
26 Aug 2023
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