One pixel attack for fooling deep neural networks

24 October 2017

Jiawei Su

Danilo Vasconcellos Vargas

Kouichi Sakurai

AAML

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Papers citing "One pixel attack for fooling deep neural networks"

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Title
Role of Spatial Context in Adversarial Robustness for Object Detection Aniruddha Saha Akshayvarun Subramanya Koninika Patil Hamed Pirsiavash ObjD AAML 32 53 0 30 Sep 2019
They Might NOT Be Giants: Crafting Black-Box Adversarial Examples with Fewer Queries Using Particle Swarm Optimization Rayan Mosli M. Wright Bo Yuan Yin Pan AAML 19 16 0 16 Sep 2019
Adversarial Attack on Skeleton-based Human Action Recognition Jian Liu Naveed Akhtar Ajmal Mian AAML 27 68 0 14 Sep 2019
Sparse and Imperceivable Adversarial Attacks Francesco Croce Matthias Hein AAML 39 199 0 11 Sep 2019
DAPAS : Denoising Autoencoder to Prevent Adversarial attack in Semantic Segmentation Seungju Cho Tae Joon Jun Byungsoo Oh Daeyoung Kim 27 31 0 14 Aug 2019
Once a MAN: Towards Multi-Target Attack via Learning Multi-Target Adversarial Network Once Jiangfan Han Xiaoyi Dong Ruimao Zhang Dongdong Chen Weiming Zhang Nenghai Yu Ping Luo Xiaogang Wang AAML 24 28 0 14 Aug 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 23 230 0 24 Jul 2019
Measuring the Transferability of Adversarial Examples D. Petrov Timothy M. Hospedales SILM AAML 20 23 0 14 Jul 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack Francesco Croce Matthias Hein AAML 43 475 0 03 Jul 2019
Mechanisms of Artistic Creativity in Deep Learning Neural Networks L. Wyse AI4CE 15 11 0 30 Jun 2019
Evolving Robust Neural Architectures to Defend from Adversarial Attacks Shashank Kotyan Danilo Vasconcellos Vargas OOD AAML 24 36 0 27 Jun 2019
Losing Confidence in Quality: Unspoken Evolution of Computer Vision Services Alex Cummaudo Rajesh Vasa J. Grundy Mohamed Abdelrazek A. Cain 29 19 0 18 Jun 2019
Evolutionary Trigger Set Generation for DNN Black-Box Watermarking Jiabao Guo M. Potkonjak AAML WIGM 26 15 0 11 Jun 2019
Risks from Learned Optimization in Advanced Machine Learning Systems Evan Hubinger Chris van Merwijk Vladimir Mikulik Joar Skalse Scott Garrabrant 45 145 0 05 Jun 2019
The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to be More Effective at Data Analysis Cynthia Rudin David Carlson HAI 30 34 0 04 Jun 2019
Enhancing Transformation-based Defenses using a Distribution Classifier C. Kou H. Lee E. Chang Teck Khim Ng 37 3 0 01 Jun 2019
Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward A. Qayyum Muhammad Usama Junaid Qadir Ala I. Al-Fuqaha AAML 27 187 0 29 May 2019
Provably scale-covariant continuous hierarchical networks based on scale-normalized differential expressions coupled in cascade T. Lindeberg 27 19 0 29 May 2019
Body Shape Privacy in Images: Understanding Privacy and Preventing Automatic Shape Extraction Hosnieh Sattar Katharina Krombholz Gerard Pons-Moll Mario Fritz 3DH 30 3 0 27 May 2019
Enhancing Adversarial Defense by k-Winners-Take-All Chang Xiao Peilin Zhong Changxi Zheng AAML 24 97 0 25 May 2019
A framework for the extraction of Deep Neural Networks by leveraging public data Soham Pal Yash Gupta Aditya Shukla Aditya Kanade S. Shevade V. Ganapathy FedML MLAU MIACV 36 56 0 22 May 2019
Taking Care of The Discretization Problem: A Comprehensive Study of the Discretization Problem and A Black-Box Adversarial Attack in Discrete Integer Domain Lei Bu Yuchao Duan Fu Song Zhe Zhao AAML 37 18 0 19 May 2019
Robustification of deep net classifiers by key based diversified aggregation with pre-filtering O. Taran Shideh Rezaeifar T. Holotyak Slava Voloshynovskiy AAML 30 1 0 14 May 2019
POBA-GA: Perturbation Optimized Black-Box Adversarial Attacks via Genetic Algorithm Jinyin Chen Mengmeng Su Shijing Shen Hui Xiong Haibin Zheng AAML 22 67 0 01 May 2019
Perceptual Attention-based Predictive Control Keuntaek Lee G. N. An Viacheslav Zakharov Evangelos A. Theodorou 15 19 0 26 Apr 2019
Beyond Explainability: Leveraging Interpretability for Improved Adversarial Learning Devinder Kumar Ibrahim Ben Daya Kanav Vats Jeffery Feng Graham W. Taylor Alexander Wong AAML 19 1 0 21 Apr 2019
Efficient Decision-based Black-box Adversarial Attacks on Face Recognition Yinpeng Dong Hang Su Baoyuan Wu Zhifeng Li Wen Liu Tong Zhang Jun Zhu CVBM AAML 28 405 0 09 Apr 2019
On the Vulnerability of CNN Classifiers in EEG-Based BCIs Xiao Zhang Dongrui Wu AAML 24 82 0 31 Mar 2019
Adversarial camera stickers: A physical camera-based attack on deep learning systems Juncheng Billy Li Frank R. Schmidt J. Zico Kolter AAML 11 164 0 21 Mar 2019
Neural Network Model Extraction Attacks in Edge Devices by Hearing Architectural Hints Xing Hu Ling Liang Lei Deng Shuangchen Li Xinfeng Xie Yu Ji Yufei Ding Chang Liu T. Sherwood Yuan Xie AAML MLAU 23 36 0 10 Mar 2019
Adversarial Attack and Defense on Point Sets Jiancheng Yang Qiang Zhang Rongyao Fang Bingbing Ni Jinxian Liu Qi Tian 3DPC 24 122 0 28 Feb 2019
Design of intentional backdoors in sequential models Zhaoyuan Yang N. Iyer Johan Reimann Nurali Virani SILM AAML 19 38 0 26 Feb 2019
Quantifying Perceptual Distortion of Adversarial Examples Matt Jordan N. Manoj Surbhi Goel A. Dimakis 19 39 0 21 Feb 2019
Weighted-Sampling Audio Adversarial Example Attack Xiaolei Liu Xiaosong Zhang Kun Wan Qingxin Zhu Yufei Ding DiffM AAML 36 36 0 26 Jan 2019
A Black-box Attack on Neural Networks Based on Swarm Evolutionary Algorithm Xiaolei Liu Yuheng Luo Xiaosong Zhang Qingxin Zhu AAML 24 16 0 26 Jan 2019
Universal Rules for Fooling Deep Neural Networks based Text Classification Di Li Danilo Vasconcellos Vargas Kouichi Sakurai AAML 21 11 0 22 Jan 2019
Interpretable CNNs for Object Classification Quanshi Zhang Xin Eric Wang Ying Nian Wu Huilin Zhou Song-Chun Zhu 24 54 0 08 Jan 2019
Ten ways to fool the masses with machine learning F. Minhas Amina Asif Asa Ben-Hur FedML HAI 33 5 0 07 Jan 2019
Mining Interpretable AOG Representations from Convolutional Networks via Active Question Answering Quanshi Zhang Ruiming Cao Ying Nian Wu Song-Chun Zhu 19 14 0 18 Dec 2018
Adversarial Framing for Image and Video Classification Konrad Zolna Michal Zajac Negar Rostamzadeh Pedro H. O. Pinheiro AAML 30 60 0 11 Dec 2018
Data Fine-tuning S. Chhabra P. Majumdar Mayank Vatsa Richa Singh AAML 20 13 0 10 Dec 2018
Strike (with) a Pose: Neural Networks Are Easily Fooled by Strange Poses of Familiar Objects Michael A. Alcorn Melvin Johnson Zhitao Gong Chengfei Wang Long Mai Naveen Ari Stella Laurenzo 47 299 0 28 Nov 2018
Enhanced Expressive Power and Fast Training of Neural Networks by Random Projections Jian-Feng Cai Dong Li Jiaze Sun Ke Wang 30 5 0 22 Nov 2018
Injecting and removing malignant features in mammography with CycleGAN: Investigation of an automated adversarial attack using neural networks Anton S. Becker Lukás Jendele Ondrej Skopek N. Berger Soleen Ghafoor M. Marcon E. Konukoglu MedIm 18 4 0 19 Nov 2018
Deep Q learning for fooling neural networks Mandar M. Kulkarni 27 0 0 13 Nov 2018
Improving Adversarial Robustness by Encouraging Discriminative Features Chirag Agarwal Anh Totti Nguyen Dan Schonfeld OOD 22 5 0 01 Nov 2018
Efficient Two-Step Adversarial Defense for Deep Neural Networks Ting-Jui Chang Yukun He Peng Li AAML 25 11 0 08 Oct 2018
Knowledge-guided Semantic Computing Network Guangming Shi Zhongqiang Zhang Dahua Gao Xuemei Xie Yihao Feng Xinrui Ma Danhua Liu 20 8 0 29 Sep 2018
Are You Tampering With My Data? Michele Alberti Vinaychandran Pondenkandath Marcel Würsch Manuel Bouillon Mathias Seuret Rolf Ingold Marcus Liwicki AAML 37 19 0 21 Aug 2018
Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer Hsueh-Ti Derek Liu Michael Tao Chun-Liang Li Derek Nowrouzezahrai Alec Jacobson AAML 42 13 0 08 Aug 2018