DeepFool: a simple and accurate method to fool deep neural networks

14 November 2015

Seyed-Mohsen Moosavi-Dezfooli

Papers citing "DeepFool: a simple and accurate method to fool deep neural networks"

50 / 905 papers shown

Title
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses Joana Cabral Costa Tiago Roxo Hugo Manuel Proença Pedro R. M. Inácio AAML 54 51 0 18 May 2023
Adversarial Amendment is the Only Force Capable of Transforming an Enemy into a Friend Chong Yu Tao Chen Zhongxue Gan AAML 23 1 0 18 May 2023
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 31 2 0 08 May 2023
A Comprehensive Study on Dataset Distillation: Performance, Privacy, Robustness and Fairness Zongxiong Chen Jiahui Geng Derui Zhu Herbert Woisetschlaeger Qing Li Sonja Schimmler Ruben Mayer Chunming Rong DD 28 9 0 05 May 2023
Single Node Injection Label Specificity Attack on Graph Neural Networks via Reinforcement Learning Dayuan Chen Jian Zhang Yuqian Lv Jinhuan Wang Hongjie Ni Shanqing Yu Zhen Wang Qi Xuan AAML 33 3 0 04 May 2023
Stochastic MPC Based Attacks on Object Tracking in Autonomous Driving Systems Sourav Sinha M. Farhood AAML 22 0 0 21 Apr 2023
Physical Knowledge Enhanced Deep Neural Network for Sea Surface Temperature Prediction Yuxin Meng Feng Gao Eric Rigall Ran Dong Junyu Dong Q. Du 29 20 0 19 Apr 2023
Implementing Responsible AI: Tensions and Trade-Offs Between Ethics Aspects Conrad Sanderson David M. Douglas Qinghua Lu 43 12 0 17 Apr 2023
Generating Adversarial Attacks in the Latent Space Nitish Shukla Sudipta Banerjee 33 8 0 10 Apr 2023
Randomized Adversarial Style Perturbations for Domain Generalization Taehoon Kim Bohyung Han AAML 38 2 0 04 Apr 2023
Improving Fast Adversarial Training with Prior-Guided Knowledge Xiaojun Jia Yong Zhang Xingxing Wei Baoyuan Wu Ke Ma Jue Wang Xiaochun Cao AAML 41 26 0 01 Apr 2023
Anti-DreamBooth: Protecting users from personalized text-to-image synthesis T. Le Hao Phung Thuan Hoang Nguyen Quan Dao Ngoc N. Tran Anh Tran 28 92 0 27 Mar 2023
CAT:Collaborative Adversarial Training Xingbin Liu Huafeng Kuang Xianming Lin Yongjian Wu Rongrong Ji AAML 27 4 0 27 Mar 2023
AdvCheck: Characterizing Adversarial Examples via Local Gradient Checking Ruoxi Chen Haibo Jin Jinyin Chen Haibin Zheng AAML 16 0 0 25 Mar 2023
Optimization and Optimizers for Adversarial Robustness Hengyue Liang Buyun Liang Le Peng Ying Cui Tim Mitchell Ju Sun AAML 28 5 0 23 Mar 2023
Decentralized Adversarial Training over Graphs Ying Cao Elsa Rizk Stefan Vlaski Ali H. Sayed AAML 45 1 0 23 Mar 2023
AdaptGuard: Defending Against Universal Attacks for Model Adaptation Lijun Sheng Jian Liang Ran He Zilei Wang Tien-Ping Tan AAML 53 5 0 19 Mar 2023
Adversarial Counterfactual Visual Explanations Guillaume Jeanneret Loïc Simon F. Jurie DiffM 41 27 0 17 Mar 2023
Can Adversarial Examples Be Parsed to Reveal Victim Model Information? Yuguang Yao Jiancheng Liu Yifan Gong Xiaoming Liu Yanzhi Wang X. Lin Sijia Liu AAML MLAU 42 1 0 13 Mar 2023
Boosting Adversarial Attacks by Leveraging Decision Boundary Information Boheng Zeng LianLi Gao Qilong Zhang Chaoqun Li JingKuan Song Shuaiqi Jing AAML 25 2 0 10 Mar 2023
Decision-BADGE: Decision-based Adversarial Batch Attack with Directional Gradient Estimation Geunhyeok Yu Minwoo Jeon Hyoseok Hwang AAML 24 1 0 09 Mar 2023
Testing the Channels of Convolutional Neural Networks Kang Choi Donghyun Son Younghoon Kim Jiwon Seo 33 1 0 06 Mar 2023
Targeted Adversarial Attacks against Neural Machine Translation Sahar Sadrizadeh AmirHossein Dabiri Aghdam Ljiljana Dolamic P. Frossard AAML 35 12 0 02 Mar 2023
Implicit Poisoning Attacks in Two-Agent Reinforcement Learning: Adversarial Policies for Training-Time Attacks Mohammad Mohammadi Jonathan Nöther Debmalya Mandal Adish Singla Goran Radanović AAML OffRL 35 9 0 27 Feb 2023
CBA: Contextual Background Attack against Optical Aerial Detection in the Physical World Jiawei Lian Xiaofei Wang Yuru Su Mingyang Ma Shaohui Mei AAML 30 32 0 27 Feb 2023
Uncertainty Injection: A Deep Learning Method for Robust Optimization W. Cui Wei Yu UQCV OOD 27 6 0 23 Feb 2023
Interpretable Spectrum Transformation Attacks to Speaker Recognition Jiadi Yao H. Luo Xiao-Lei Zhang AAML 34 1 0 21 Feb 2023
Attacks in Adversarial Machine Learning: A Systematic Survey from the Life-cycle Perspective Baoyuan Wu Zihao Zhu Li Liu Qingshan Liu Zhaofeng He Siwei Lyu AAML 49 21 0 19 Feb 2023
TransFool: An Adversarial Attack against Neural Machine Translation Models Sahar Sadrizadeh Ljiljana Dolamic P. Frossard SILM AAML 46 12 0 02 Feb 2023
Universal Soldier: Using Universal Adversarial Perturbations for Detecting Backdoor Attacks Xiaoyun Xu Oguzhan Ersoy S. Picek AAML 32 2 0 01 Feb 2023
Benchmarking Robustness to Adversarial Image Obfuscations Florian Stimberg Ayan Chakrabarti Chun-Ta Lu Hussein Hazimeh Otilia Stretcu ... Merve Kaya Cyrus Rashtchian Ariel Fuxman Mehmet Tek Sven Gowal AAML 37 10 0 30 Jan 2023
Improving Adversarial Transferability with Scheduled Step Size and Dual Example Zeliang Zhang Peihan Liu Xiaosen Wang Chenliang Xu AAML 37 3 0 30 Jan 2023
Lateralized Learning for Multi-Class Visual Classification Tasks Abubakar Siddique Will N. Browne Gina M. Grimshaw 31 2 0 30 Jan 2023
Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing Yatong Bai Brendon G. Anderson Aerin Kim Somayeh Sojoudi AAML 41 18 0 29 Jan 2023
Mitigating Adversarial Effects of False Data Injection Attacks in Power Grid Farhin Farhad Riya Shahinul Hoque Jinyuan Stella Sun Jiangnan Li Hairong Qi Hairong Qi AAML AI4CE 49 0 0 29 Jan 2023
Attacking Important Pixels for Anchor-free Detectors Yunxu Xie Shu Hu Xin Wang Quanyu Liao Bin Zhu Xi Wu Siwei Lyu ObjD AAML 40 2 0 26 Jan 2023
On the feasibility of attacking Thai LPR systems with adversarial examples Chissanupong Jiamsuchon Jakapan Suaboot Norrathep Rattanavipanon AAML 14 0 0 13 Jan 2023
Beckman Defense A. V. Subramanyam OOD AAML 42 0 0 04 Jan 2023
ExploreADV: Towards exploratory attack for Neural Networks Tianzuo Luo Yuyi Zhong S. Khoo AAML 24 1 0 01 Jan 2023
Tracing the Origin of Adversarial Attack for Forensic Investigation and Deterrence Han Fang Jiyi Zhang Yupeng Qiu Ke Xu Chengfang Fang E. Chang AAML 33 2 0 31 Dec 2022
Adversarial attacks and defenses on ML- and hardware-based IoT device fingerprinting and identification Pedro Miguel Sánchez Sánchez Alberto Huertas Celdrán Gérome Bovet Gregorio Martínez Pérez AAML 29 17 0 30 Dec 2022
Confidence-aware Training of Smoothed Classifiers for Certified Robustness Jongheon Jeong Seojin Kim Jinwoo Shin AAML 21 7 0 18 Dec 2022
Adversarial Example Defense via Perturbation Grading Strategy Shaowei Zhu Wanli Lyu Bin Li Z. Yin Bin Luo AAML 37 1 0 16 Dec 2022
Understanding Zero-Shot Adversarial Robustness for Large-Scale Models Chengzhi Mao Scott Geng Junfeng Yang Xin Eric Wang Carl Vondrick VLM 44 60 0 14 Dec 2022
SAIF: Sparse Adversarial and Imperceptible Attack Framework Tooba Imtiaz Morgan Kohler Jared Miller Zifeng Wang Octavia Camps Mario Sznaier Octavia Camps Jennifer Dy AAML 34 0 0 14 Dec 2022
Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial Detection P. Lorenz M. Keuper J. Keuper AAML 24 7 0 13 Dec 2022
REAP: A Large-Scale Realistic Adversarial Patch Benchmark Nabeel Hingun Chawin Sitawarin Jerry Li David Wagner AAML 31 14 0 12 Dec 2022
General Adversarial Defense Against Black-box Attacks via Pixel Level and Feature Level Distribution Alignments Xiaogang Xu Hengshuang Zhao Philip Torr Jiaya Jia AAML 39 2 0 11 Dec 2022
Targeted Adversarial Attacks against Neural Network Trajectory Predictors Kai Liang Tan Jun Wang Y. Kantaros AAML 38 14 0 08 Dec 2022
$Multiple Perturbation Attack: Attack Pixelwise Under Different $\ell_p$-norms For Better Adversarial Performance$ Multiple Perturbation Attack: Attack Pixelwise Under Different $\ell_p$ -norms For Better Adversarial Performance Ngoc N. Tran Anh Tuan Bui Dinh Q. Phung Trung Le AAML 34 1 0 05 Dec 2022