Adversarial examples in the physical world

8 July 2016

Papers citing "Adversarial examples in the physical world"

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Title
Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography Zihan Wang Olivia Byrnes Hu Wang Ruoxi Sun Congbo Ma Huaming Chen Qi Wu Minhui Xue 19 55 0 20 Jul 2021
Automatic Fairness Testing of Neural Classifiers through Adversarial Sampling Peixin Zhang Jingyi Wang Jun Sun Xinyu Wang Guoliang Dong Xingen Wang Ting Dai Jin Song Dong 13 24 0 17 Jul 2021
Correlation Analysis between the Robustness of Sparse Neural Networks and their Random Hidden Structural Priors M. B. Amor Julian Stier Michael Granitzer OOD AAML 9 2 0 13 Jul 2021
Stateful Detection of Model Extraction Attacks Soham Pal Yash Gupta Aditya Kanade S. Shevade MLAU 57 24 0 12 Jul 2021
Out of Distribution Detection and Adversarial Attacks on Deep Neural Networks for Robust Medical Image Analysis Anisie Uwimana Ransalu Senanayake OOD MedIm 23 21 0 10 Jul 2021
Learning to Detect Adversarial Examples Based on Class Scores Tobias Uelwer Félix D. P. Michels Oliver De Candido AAML 20 1 0 09 Jul 2021
Universal 3-Dimensional Perturbations for Black-Box Attacks on Video Recognition Systems Shangyu Xie Han Wang Yu Kong Yuan Hong AAML 19 25 0 09 Jul 2021
Output Randomization: A Novel Defense for both White-box and Black-box Adversarial Models Daniel Park Haidar Khan Azer Khan Alex Gittens B. Yener AAML 18 1 0 08 Jul 2021
ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients Alessandro Cappelli Julien Launay Laurent Meunier Ruben Ohana Iacopo Poli AAML 29 4 0 06 Jul 2021
On Robustness of Lane Detection Models to Physical-World Adversarial Attacks in Autonomous Driving Takami Sato Qi Alfred Chen AAML ELM 37 6 0 06 Jul 2021
Self-Adversarial Training incorporating Forgery Attention for Image Forgery Localization Longhao Zhuo Shunquan Tan Bin Li Jiwu Huang AAML 11 71 0 06 Jul 2021
Robust Online Convex Optimization in the Presence of Outliers T. Erven Sarah Sachs Wouter M. Koolen W. Kotłowski 17 8 0 05 Jul 2021
Boosting Transferability of Targeted Adversarial Examples via Hierarchical Generative Networks Xiao Yang Yinpeng Dong Tianyu Pang Hang Su Jun Zhu AAML 38 38 0 05 Jul 2021
Evaluating the Cybersecurity Risk of Real World, Machine Learning Production Systems Ron Bitton Nadav Maman Inderjeet Singh Satoru Momiyama Yuval Elovici A. Shabtai 13 19 0 05 Jul 2021
Demiguise Attack: Crafting Invisible Semantic Adversarial Perturbations with Perceptual Similarity Yajie Wang Shangbo Wu Wenyi Jiang Shengang Hao Yu-an Tan Quan-xin Zhang AAML 6 27 0 03 Jul 2021
Using Anomaly Feature Vectors for Detecting, Classifying and Warning of Outlier Adversarial Examples Nelson Manohar-Alers Ryan Feng Sahib Singh Jiguo Song Atul Prakash AAML 27 1 0 01 Jul 2021
Single-Step Adversarial Training for Semantic Segmentation D. Wiens Barbara Hammer SSeg AAML 26 1 0 30 Jun 2021
Bio-Inspired Adversarial Attack Against Deep Neural Networks B. Xi Yujie Chen Fei Fan Zhan Tu Xinyan Deng AAML 18 1 0 30 Jun 2021
Adversarial Machine Learning for Cybersecurity and Computer Vision: Current Developments and Challenges B. Xi AAML 24 28 0 30 Jun 2021
Understanding Adversarial Examples Through Deep Neural Network's Response Surface and Uncertainty Regions Juan Shu B. Xi Charles A. Kamhoua AAML 19 0 0 30 Jun 2021
Local Reweighting for Adversarial Training Ruize Gao Feng Liu Kaiwen Zhou Gang Niu Bo Han James Cheng AAML OOD 25 6 0 30 Jun 2021
Attention Aware Wavelet-based Detection of Morphed Face Images Poorya Aghdaie Baaria Chaudhary Sobhan Soleymani J. Dawson Nasser M. Nasrabadi CVBM 15 29 0 29 Jun 2021
Inconspicuous Adversarial Patches for Fooling Image Recognition Systems on Mobile Devices Tao Bai Jinqi Luo Jun Zhao AAML 31 30 0 29 Jun 2021
ASK: Adversarial Soft k-Nearest Neighbor Attack and Defense Ren Wang Tianqi Chen Philip Yao Sijia Liu I. Rajapakse Alfred Hero AAML OOD 6 5 0 27 Jun 2021
Who is Responsible for Adversarial Defense? Kishor Datta Gupta D. Dasgupta AAML 27 2 0 27 Jun 2021
Countering Adversarial Examples: Combining Input Transformation and Noisy Training Cheng Zhang Pan Gao AAML 25 3 0 25 Jun 2021
Minimum sharpness: Scale-invariant parameter-robustness of neural networks Hikaru Ibayashi Takuo Hamaguchi Masaaki Imaizumi 25 5 0 23 Jun 2021
NCIS: Neural Contextual Iterative Smoothing for Purifying Adversarial Perturbations Sungmin Cha Naeun Ko Young Joon Yoo Taesup Moon AAML 26 2 0 22 Jun 2021
Graceful Degradation and Related Fields J. Dymond 31 4 0 21 Jun 2021
Attack to Fool and Explain Deep Networks Naveed Akhtar M. Jalwana Bennamoun Ajmal Mian AAML 29 33 0 20 Jun 2021
Accumulative Poisoning Attacks on Real-time Data Tianyu Pang Xiao Yang Yinpeng Dong Hang Su Jun Zhu 32 20 0 18 Jun 2021
Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis Martin Pawelczyk Chirag Agarwal Shalmali Joshi Sohini Upadhyay Himabindu Lakkaraju AAML 32 51 0 18 Jun 2021
Towards interpreting computer vision based on transformation invariant optimization Chen Li Jinzhe Jiang Xin Zhang Tonghuan Zhang Yaqian Zhao Dong-Liang Jiang Rengang Li AI4CE 12 0 0 18 Jun 2021
Light Lies: Optical Adversarial Attack Kyulim Kim Jeong-Soo Kim Seung-Ri Song Jun-Ho Choi Chul-Min Joo Jong-Seok Lee AAML 27 5 0 18 Jun 2021
Analyzing Adversarial Robustness of Deep Neural Networks in Pixel Space: a Semantic Perspective Lina Wang Xingshu Chen Yulong Wang Yawei Yue Yi Zhu Xuemei Zeng Wei Wang AAML 31 0 0 18 Jun 2021
Adversarial Detection Avoidance Attacks: Evaluating the robustness of perceptual hashing-based client-side scanning Shubham Jain Ana-Maria Cretu Yves-Alexandre de Montjoye 16 33 0 17 Jun 2021
Adversarial Visual Robustness by Causal Intervention Kaihua Tang Ming Tao Hanwang Zhang CML AAML 27 21 0 17 Jun 2021
Evaluating the Robustness of Bayesian Neural Networks Against Different Types of Attacks Yutian Pang Sheng Cheng Jueming Hu Yongming Liu AAML 20 12 0 17 Jun 2021
Towards Adversarial Robustness via Transductive Learning Jiefeng Chen Yang Guo Xi Wu Tianqi Li Qicheng Lao Yingyu Liang S. Jha AAML 18 5 0 15 Jun 2021
Adversarial Attacks on Deep Models for Financial Transaction Records I. Fursov Matvey Morozov N. Kaploukhaya Elizaveta Kovtun Rodrigo Rivera-Castro Gleb Gusev Dmitrii Babaev Ivan Kireev Alexey Zaytsev E. Burnaev AAML 38 38 0 15 Jun 2021
Probabilistic Margins for Instance Reweighting in Adversarial Training Qizhou Wang Feng Liu Bo Han Tongliang Liu Chen Gong Gang Niu Mingyuan Zhou Masashi Sugiyama AAML 37 61 0 15 Jun 2021
Controlling Neural Networks with Rule Representations Sungyong Seo Sercan Ö. Arik Jinsung Yoon Xiang Zhang Kihyuk Sohn Tomas Pfister OOD AI4CE 32 35 0 14 Jun 2021
Audio Attacks and Defenses against AED Systems -- A Practical Study Rodrigo Augusto dos Santos Shirin Nilizadeh AAML 25 2 0 14 Jun 2021
Certification of embedded systems based on Machine Learning: A survey Guillaume Vidot Christophe Gabreau I. Ober Iulian Ober 11 12 0 14 Jun 2021
Selection of Source Images Heavily Influences the Effectiveness of Adversarial Attacks Utku Ozbulak Esla Timothy Anzaku W. D. Neve Arnout Van Messem AAML 30 10 0 14 Jun 2021
Relaxing Local Robustness Klas Leino Matt Fredrikson AAML 18 8 0 11 Jun 2021
Progressive-Scale Boundary Blackbox Attack via Projective Gradient Estimation Jiawei Zhang Linyi Li Huichen Li Xiaolu Zhang Shuang Yang Yangqiu Song AAML 17 17 0 10 Jun 2021
We Can Always Catch You: Detecting Adversarial Patched Objects WITH or WITHOUT Signature Binxiu Liang Jiachun Li Jianjun Huang AAML 33 12 0 09 Jun 2021
HASI: Hardware-Accelerated Stochastic Inference, A Defense Against Adversarial Machine Learning Attacks Mohammad Hossein Samavatian Saikat Majumdar Kristin Barber R. Teodorescu AAML 26 4 0 09 Jun 2021
Reveal of Vision Transformers Robustness against Adversarial Attacks Ahmed Aldahdooh W. Hamidouche Olivier Déforges ViT 15 57 0 07 Jun 2021