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Keeping the Bad Guys Out: Protecting and Vaccinating Deep Learning with
  JPEG Compression

Keeping the Bad Guys Out: Protecting and Vaccinating Deep Learning with JPEG Compression

8 May 2017
Nilaksh Das
Madhuri Shanbhogue
Shang-Tse Chen
Fred Hohman
Li-Wei Chen
Michael E. Kounavis
Duen Horng Chau
    AAML
ArXiv (abs)PDFHTML

Papers citing "Keeping the Bad Guys Out: Protecting and Vaccinating Deep Learning with JPEG Compression"

50 / 161 papers shown
Title
Active Adversarial Noise Suppression for Image Forgery Localization
Active Adversarial Noise Suppression for Image Forgery Localization
Rongxuan Peng
Shunquan Tan
Xianbo Mo
Alex C. Kot
Jiwu Huang
AAML
7
0
0
15 Jun 2025
Efficiency Robustness of Dynamic Deep Learning Systems
Efficiency Robustness of Dynamic Deep Learning Systems
Ravishka Rathnasuriya
Tingxi Li
Zexin Xu
Zihe Song
Mirazul Haque
Simin Chen
Wei Yang
AAMLSILM
138
0
0
12 Jun 2025
DP-TRAE: A Dual-Phase Merging Transferable Reversible Adversarial Example for Image Privacy Protection
DP-TRAE: A Dual-Phase Merging Transferable Reversible Adversarial Example for Image Privacy Protection
Xia Du
Jiajie Zhu
Jizhe Zhou
Chi-Man Pun
Zheng Lin
Cong Wu
Zhaoyu Chen
Jun Luo
AAML
68
0
0
11 May 2025
Quantum Computing Supported Adversarial Attack-Resilient Autonomous Vehicle Perception Module for Traffic Sign Classification
Quantum Computing Supported Adversarial Attack-Resilient Autonomous Vehicle Perception Module for Traffic Sign Classification
Reek Majumder
M. Chowdhury
S. Khan
Zadid Khan
Fahim Ahmad
Frank Ngeni
G. Comert
Judith Mwakalonge
Dimitra Michalaka
AAML
40
0
0
17 Apr 2025
Rethinking Robustness in Machine Learning: A Posterior Agreement Approach
Rethinking Robustness in Machine Learning: A Posterior Agreement Approach
João B. S. Carvalho
Alessandro Torcinovich
Victor Jimenez Rodriguez
Antonio Emanuele Cinà
Carlos Cotrini
Lea Schönherr
J. M. Buhmann
OOD
111
0
0
20 Mar 2025
Long-tailed Adversarial Training with Self-Distillation
Seungju Cho
Hongsin Lee
Changick Kim
AAMLTTA
498
0
0
09 Mar 2025
Prompt-driven Transferable Adversarial Attack on Person Re-Identification with Attribute-aware Textual Inversion
Prompt-driven Transferable Adversarial Attack on Person Re-Identification with Attribute-aware Textual Inversion
Yuan Bian
Min Liu
Yunqi Yi
Xueping Wang
Yaonan Wang
AAML
92
0
0
27 Feb 2025
Learning from Convolution-based Unlearnable Datasets
Learning from Convolution-based Unlearnable Datasets
Dohyun Kim
Pedro Sandoval-Segura
MU
172
1
0
04 Nov 2024
JPEG Inspired Deep Learning
JPEG Inspired Deep Learning
Ahmed H. Salamah
Kaixiang Zheng
Yiwen Liu
En-Hui Yang
94
1
0
09 Oct 2024
Unrevealed Threats: A Comprehensive Study of the Adversarial Robustness
  of Underwater Image Enhancement Models
Unrevealed Threats: A Comprehensive Study of the Adversarial Robustness of Underwater Image Enhancement Models
Siyu Zhai
Zhibo He
Xiaofeng Cong
Junming Hou
Jie Gui
Jian Wei You
Xin Gong
James Tin-Yau Kwok
Yuan Yan Tang
AAML
56
0
0
10 Sep 2024
Learning to Learn Transferable Generative Attack for Person Re-Identification
Learning to Learn Transferable Generative Attack for Person Re-Identification
Yuan Bian
Min Liu
Xueping Wang
Yunfeng Ma
Yaonan Wang
AAMLOOD
161
1
0
06 Sep 2024
Scaling Training Data with Lossy Image Compression
Scaling Training Data with Lossy Image Compression
Katherine L. Mentzer
Andrea Montanari
46
0
0
25 Jul 2024
Artificial Immune System of Secure Face Recognition Against Adversarial
  Attacks
Artificial Immune System of Secure Face Recognition Against Adversarial Attacks
Min Ren
Yunlong Wang
Yuhao Zhu
Yongzhen Huang
Zhenan Sun
Qi Li
Tieniu Tan
112
4
0
26 Jun 2024
I Don't Know You, But I Can Catch You: Real-Time Defense against Diverse
  Adversarial Patches for Object Detectors
I Don't Know You, But I Can Catch You: Real-Time Defense against Diverse Adversarial Patches for Object Detectors
Zijin Lin
Yue Zhao
Kai Chen
Jinwen He
AAML
56
1
0
12 Jun 2024
Robust width: A lightweight and certifiable adversarial defense
Robust width: A lightweight and certifiable adversarial defense
Jonathan Peck
Bart Goossens
AAML
76
2
0
24 May 2024
Adversarial purification for no-reference image-quality metrics:
  applicability study and new methods
Adversarial purification for no-reference image-quality metrics: applicability study and new methods
Aleksandr Gushchin
Anna Chistyakova
Vladislav Minashkin
Anastasia Antsiferova
D. Vatolin
80
3
0
10 Apr 2024
Defenses in Adversarial Machine Learning: A Survey
Defenses in Adversarial Machine Learning: A Survey
Baoyuan Wu
Shaokui Wei
Mingli Zhu
Meixi Zheng
Zihao Zhu
Ruotong Wang
Hongrui Chen
Danni Yuan
Li Liu
Qingshan Liu
AAML
118
14
0
13 Dec 2023
Indirect Gradient Matching for Adversarial Robust Distillation
Indirect Gradient Matching for Adversarial Robust Distillation
Hongsin Lee
Seungju Cho
Changick Kim
AAMLFedML
102
2
0
06 Dec 2023
Towards Improving Robustness Against Common Corruptions in Object
  Detectors Using Adversarial Contrastive Learning
Towards Improving Robustness Against Common Corruptions in Object Detectors Using Adversarial Contrastive Learning
Shashank Kotyan
Danilo Vasconcellos Vargas
AAML
42
0
0
14 Nov 2023
A reading survey on adversarial machine learning: Adversarial attacks
  and their understanding
A reading survey on adversarial machine learning: Adversarial attacks and their understanding
Shashank Kotyan
AAML
66
6
0
07 Aug 2023
Advancing Adversarial Training by Injecting Booster Signal
Advancing Adversarial Training by Injecting Booster Signal
Hong Joo Lee
Youngjoon Yu
Yonghyun Ro
AAML
66
3
0
27 Jun 2023
Area is all you need: repeatable elements make stronger adversarial
  attacks
Area is all you need: repeatable elements make stronger adversarial attacks
D. Niederhut
AAML
59
0
0
13 Jun 2023
Revisiting the Trade-off between Accuracy and Robustness via Weight
  Distribution of Filters
Revisiting the Trade-off between Accuracy and Robustness via Weight Distribution of Filters
Xingxing Wei
Shiji Zhao
Bo li
AAML
112
7
0
06 Jun 2023
Exploring the Vulnerabilities of Machine Learning and Quantum Machine
  Learning to Adversarial Attacks using a Malware Dataset: A Comparative
  Analysis
Exploring the Vulnerabilities of Machine Learning and Quantum Machine Learning to Adversarial Attacks using a Malware Dataset: A Comparative Analysis
Mst. Shapna Akter
Hossain Shahriar
Iysa Iqbal
M. Hossain
M. A. Karim
Victor A. Clincy
R. Voicu
AAML
65
8
0
31 May 2023
Adversarial Examples Detection with Enhanced Image Difference Features
  based on Local Histogram Equalization
Adversarial Examples Detection with Enhanced Image Difference Features based on Local Histogram Equalization
Z. Yin
Shaowei Zhu
Han Su
Jianteng Peng
Wanli Lyu
Bin Luo
AAML
53
2
0
08 May 2023
JPEG Compressed Images Can Bypass Protections Against AI Editing
JPEG Compressed Images Can Bypass Protections Against AI Editing
Pedro Sandoval-Segura
Jonas Geiping
Tom Goldstein
DiffM
56
11
0
05 Apr 2023
GradMDM: Adversarial Attack on Dynamic Networks
GradMDM: Adversarial Attack on Dynamic Networks
Jianhong Pan
Lin Geng Foo
Qichen Zheng
Zhipeng Fan
Hossein Rahmani
Qiuhong Ke
Jing Liu
AAML
75
7
0
01 Apr 2023
CFA: Class-wise Calibrated Fair Adversarial Training
CFA: Class-wise Calibrated Fair Adversarial Training
Zeming Wei
Yifei Wang
Yiwen Guo
Yisen Wang
AAML
101
54
0
25 Mar 2023
Image Shortcut Squeezing: Countering Perturbative Availability Poisons
  with Compression
Image Shortcut Squeezing: Countering Perturbative Availability Poisons with Compression
Zhuoran Liu
Zhengyu Zhao
Martha Larson
81
37
0
31 Jan 2023
RobustPdM: Designing Robust Predictive Maintenance against Adversarial
  Attacks
RobustPdM: Designing Robust Predictive Maintenance against Adversarial Attacks
Ayesha Siddique
Ripan Kumar Kundu
Gautam Raj Mode
K. A. Hoque
AAML
51
2
0
25 Jan 2023
DISCO: Adversarial Defense with Local Implicit Functions
DISCO: Adversarial Defense with Local Implicit Functions
Chih-Hui Ho
Nuno Vasconcelos
AAML
128
39
0
11 Dec 2022
Defending with Errors: Approximate Computing for Robustness of Deep
  Neural Networks
Defending with Errors: Approximate Computing for Robustness of Deep Neural Networks
Amira Guesmi
Ihsen Alouani
Khaled N. Khasawneh
M. Baklouti
T. Frikha
Mohamed Abid
Nael B. Abu-Ghazaleh
AAMLOOD
142
2
0
02 Nov 2022
Causal Information Bottleneck Boosts Adversarial Robustness of Deep
  Neural Network
Causal Information Bottleneck Boosts Adversarial Robustness of Deep Neural Network
Hua Hua
Jun Yan
Xi Fang
Weiquan Huang
Huilin Yin
Wancheng Ge
AAML
54
1
0
25 Oct 2022
Hindering Adversarial Attacks with Implicit Neural Representations
Hindering Adversarial Attacks with Implicit Neural Representations
Andrei A. Rusu
D. A. Calian
Sven Gowal
R. Hadsell
AAML
165
4
0
22 Oct 2022
Hierarchical Perceptual Noise Injection for Social Media Fingerprint
  Privacy Protection
Hierarchical Perceptual Noise Injection for Social Media Fingerprint Privacy Protection
Simin Li
Huangxinxin Xu
Jiakai Wang
Aishan Liu
Fazhi He
Xianglong Liu
Dacheng Tao
AAML
64
6
0
23 Aug 2022
Scale-free and Task-agnostic Attack: Generating Photo-realistic
  Adversarial Patterns with Patch Quilting Generator
Scale-free and Task-agnostic Attack: Generating Photo-realistic Adversarial Patterns with Patch Quilting Generator
Xiang Gao
Cheng Luo
Qinliang Lin
Weicheng Xie
Minmin Liu
Linlin Shen
Keerthy Kusumam
Siyang Song
47
5
0
12 Aug 2022
Rethinking Textual Adversarial Defense for Pre-trained Language Models
Rethinking Textual Adversarial Defense for Pre-trained Language Models
Jiayi Wang
Rongzhou Bao
Zhuosheng Zhang
Hai Zhao
AAMLSILM
56
11
0
21 Jul 2022
Perturbation Inactivation Based Adversarial Defense for Face Recognition
Perturbation Inactivation Based Adversarial Defense for Face Recognition
Min Ren
Yuhao Zhu
Yunlong Wang
Zhenan Sun
AAML
54
14
0
13 Jul 2022
Morphence-2.0: Evasion-Resilient Moving Target Defense Powered by
  Out-of-Distribution Detection
Morphence-2.0: Evasion-Resilient Moving Target Defense Powered by Out-of-Distribution Detection
Abderrahmen Amich
Ata Kaboudi
Birhanu Eshete
AAMLOODD
25
1
0
15 Jun 2022
Exploring Adversarial Attacks and Defenses in Vision Transformers
  trained with DINO
Exploring Adversarial Attacks and Defenses in Vision Transformers trained with DINO
Javier Rando
Nasib Naimi
Thomas Baumann
Max Mathys
AAML
53
6
0
14 Jun 2022
Attack-Agnostic Adversarial Detection
Attack-Agnostic Adversarial Detection
Jiaxin Cheng
Mohamed Hussein
J. Billa
Wael AbdAlmageed
AAML
53
0
0
01 Jun 2022
Special Session: Towards an Agile Design Methodology for Efficient,
  Reliable, and Secure ML Systems
Special Session: Towards an Agile Design Methodology for Efficient, Reliable, and Secure ML Systems
Shail Dave
Alberto Marchisio
Muhammad Abdullah Hanif
Amira Guesmi
Aviral Shrivastava
Ihsen Alouani
Mohamed Bennai
75
14
0
18 Apr 2022
Distinguishing Non-natural from Natural Adversarial Samples for More
  Robust Pre-trained Language Model
Distinguishing Non-natural from Natural Adversarial Samples for More Robust Pre-trained Language Model
Jiayi Wang
Rongzhou Bao
Zhuosheng Zhang
Hai Zhao
AAML
57
4
0
19 Mar 2022
Perception Over Time: Temporal Dynamics for Robust Image Understanding
Perception Over Time: Temporal Dynamics for Robust Image Understanding
Maryam Daniali
Edward J. Kim
AI4TS
53
6
0
11 Mar 2022
Rethinking Machine Learning Robustness via its Link with the
  Out-of-Distribution Problem
Rethinking Machine Learning Robustness via its Link with the Out-of-Distribution Problem
Abderrahmen Amich
Birhanu Eshete
OOD
25
4
0
18 Feb 2022
Lossy Compression of Noisy Data for Private and Data-Efficient Learning
Lossy Compression of Noisy Data for Private and Data-Efficient Learning
Berivan Isik
Tsachy Weissman
64
3
0
07 Feb 2022
Fooling the Eyes of Autonomous Vehicles: Robust Physical Adversarial
  Examples Against Traffic Sign Recognition Systems
Fooling the Eyes of Autonomous Vehicles: Robust Physical Adversarial Examples Against Traffic Sign Recognition Systems
Wei Jia
Zhaojun Lu
Haichun Zhang
Zhenglin Liu
Jie Wang
Gang Qu
AAML
71
53
0
17 Jan 2022
Repairing Adversarial Texts through Perturbation
Repairing Adversarial Texts through Perturbation
Guoliang Dong
Jingyi Wang
Jun Sun
Sudipta Chattopadhyay
Xinyu Wang
Ting Dai
Jie Shi
J. Dong
AAML
29
2
0
29 Dec 2021
Super-Efficient Super Resolution for Fast Adversarial Defense at the
  Edge
Super-Efficient Super Resolution for Fast Adversarial Defense at the Edge
Kartikeya Bhardwaj
Dibakar Gope
James Ward
P. Whatmough
Danny Loh
AAML
30
4
0
29 Dec 2021
Associative Adversarial Learning Based on Selective Attack
Associative Adversarial Learning Based on Selective Attack
Runqi Wang
Xiaoyue Duan
Baochang Zhang
Shenjun Xue
Wentao Zhu
David Doermann
G. Guo
AAML
70
0
0
28 Dec 2021
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