Universal adversarial perturbations

26 October 2016

Seyed-Mohsen Moosavi-Dezfooli

Papers citing "Universal adversarial perturbations"

50 / 1,266 papers shown

Title
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning Xinyun Chen Chang-rui Liu Bo-wen Li Kimberly Lu D. Song AAML SILM 44 1,808 0 15 Dec 2017
NAG: Network for Adversary Generation Konda Reddy Mopuri Utkarsh Ojha Utsav Garg R. Venkatesh Babu AAML 24 144 0 09 Dec 2017
Adversarial Examples that Fool Detectors Jiajun Lu Hussein Sibai Evan Fabry AAML 19 144 0 07 Dec 2017
Generative Adversarial Perturbations Omid Poursaeed Isay Katsman Bicheng Gao Serge J. Belongie AAML GAN WIGM 31 351 0 06 Dec 2017
Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning Hongge Chen Huan Zhang Pin-Yu Chen Jinfeng Yi Cho-Jui Hsieh GAN AAML 35 49 0 06 Dec 2017
A+D Net: Training a Shadow Detector with Adversarial Shadow Attenuation Hieu M. Le T. F. Y. Vicente Vu Nguyen Minh Hoai Dimitris Samaras 26 114 0 04 Dec 2017
Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images Tribhuvanesh Orekondy Mario Fritz Bernt Schiele PICV 24 80 0 04 Dec 2017
Improving Network Robustness against Adversarial Attacks with Compact Convolution Rajeev Ranjan S. Sankaranarayanan Carlos D. Castillo Rama Chellappa AAML 24 14 0 03 Dec 2017
Where Classification Fails, Interpretation Rises Chanh Nguyen Georgi Georgiev Yujie Ji Ting Wang AAML 15 0 0 02 Dec 2017
Measuring the tendency of CNNs to Learn Surface Statistical Regularities Jason Jo Yoshua Bengio AAML 26 249 0 30 Nov 2017
Adversary Detection in Neural Networks via Persistent Homology Thomas Gebhart Paul Schrater AAML 24 25 0 28 Nov 2017
On the Robustness of Semantic Segmentation Models to Adversarial Attacks Anurag Arnab O. Mikšík Philip Torr AAML 33 304 0 27 Nov 2017
Butterfly Effect: Bidirectional Control of Classification Performance by Small Additive Perturbation Y. Yoo Seonguk Park Junyoung Choi Sangdoo Yun Nojun Kwak AAML 24 4 0 27 Nov 2017
Adversarial Attacks Beyond the Image Space Fangyin Wei Chenxi Liu Yu-Siang Wang Weichao Qiu Lingxi Xie Yu-Wing Tai Chi-Keung Tang Alan Yuille AAML 41 145 0 20 Nov 2017
Defense against Universal Adversarial Perturbations Naveed Akhtar Jian Liu Ajmal Mian AAML 28 207 0 16 Nov 2017
Machine vs Machine: Minimax-Optimal Defense Against Adversarial Examples Jihun Hamm Akshay Mehra AAML 29 7 0 12 Nov 2017
LatentPoison - Adversarial Attacks On The Latent Space Antonia Creswell Anil A. Bharath B. Sengupta AAML OOD 22 20 0 08 Nov 2017
Adversarial Frontier Stitching for Remote Neural Network Watermarking Erwan Le Merrer P. Pérez Gilles Trédan MLAU AAML 42 336 0 06 Nov 2017
Towards Reverse-Engineering Black-Box Neural Networks Seong Joon Oh Maximilian Augustin Bernt Schiele Mario Fritz AAML 289 3 0 06 Nov 2017
Countering Adversarial Images using Input Transformations Chuan Guo Mayank Rana Moustapha Cissé Laurens van der Maaten AAML 30 1,388 0 31 Oct 2017
Generating Natural Adversarial Examples Zhengli Zhao Dheeru Dua Sameer Singh GAN AAML 38 596 0 31 Oct 2017
Rethinking generalization requires revisiting old ideas: statistical mechanics approaches and complex learning behavior Charles H. Martin Michael W. Mahoney AI4CE 30 62 0 26 Oct 2017
One pixel attack for fooling deep neural networks Jiawei Su Danilo Vasconcellos Vargas Kouichi Sakurai AAML 24 2,306 0 24 Oct 2017
Feature-Guided Black-Box Safety Testing of Deep Neural Networks Matthew Wicker Xiaowei Huang Marta Kwiatkowska AAML 12 232 0 21 Oct 2017
ADA: A Game-Theoretic Perspective on Data Augmentation for Object Detection Sima Behpour Kris Kitani Brian Ziebart AAML 35 4 0 21 Oct 2017
Boosting Adversarial Attacks with Momentum Yinpeng Dong Fangzhou Liao Tianyu Pang Hang Su Jun Zhu Xiaolin Hu Jianguo Li AAML 26 83 0 17 Oct 2017
Standard detectors aren't (currently) fooled by physical adversarial stop signs Jiajun Lu Hussein Sibai Evan Fabry David A. Forsyth AAML 16 59 0 09 Oct 2017
Verification of Binarized Neural Networks via Inter-Neuron Factoring Chih-Hong Cheng Georg Nührenberg Chung-Hao Huang Harald Ruess AAML 25 21 0 09 Oct 2017
Fooling Vision and Language Models Despite Localization and Attention Mechanism Xiaojun Xu Xinyun Chen Chang-rui Liu Anna Rohrbach Trevor Darrell D. Song AAML 10 41 0 25 Sep 2017
Verifying Properties of Binarized Deep Neural Networks Nina Narodytska S. Kasiviswanathan L. Ryzhyk Shmuel Sagiv T. Walsh AAML 21 215 0 19 Sep 2017
A Learning and Masking Approach to Secure Learning Linh Nguyen Sky Wang Arunesh Sinha AAML 32 2 0 13 Sep 2017
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples Pin-Yu Chen Yash Sharma Huan Zhang Jinfeng Yi Cho-Jui Hsieh AAML 24 637 0 13 Sep 2017
Art of singular vectors and universal adversarial perturbations Valentin Khrulkov Ivan Oseledets AAML 27 132 0 11 Sep 2017
Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization Luis Muñoz-González Battista Biggio Ambra Demontis Andrea Paudice Vasin Wongrassamee Emil C. Lupu Fabio Roli AAML 27 625 0 29 Aug 2017
BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain Tianyu Gu Brendan Dolan-Gavitt S. Garg SILM 17 1,740 0 22 Aug 2017
Learning Universal Adversarial Perturbations with Generative Models Jamie Hayes G. Danezis AAML 13 54 0 17 Aug 2017
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models Pin-Yu Chen Huan Zhang Yash Sharma Jinfeng Yi Cho-Jui Hsieh AAML 22 1,854 0 14 Aug 2017
Robust Physical-World Attacks on Deep Learning Models Kevin Eykholt Ivan Evtimov Earlence Fernandes Bo-wen Li Amir Rahmati Chaowei Xiao Atul Prakash Tadayoshi Kohno D. Song AAML 6 590 0 27 Jul 2017
Adversarial Examples for Evaluating Reading Comprehension Systems Robin Jia Percy Liang AAML ELM 157 1,584 0 23 Jul 2017
Confidence estimation in Deep Neural networks via density modelling Akshayvarun Subramanya Suraj Srinivas R. Venkatesh Babu 22 51 0 21 Jul 2017
Efficient Defenses Against Adversarial Attacks Valentina Zantedeschi Maria-Irina Nicolae Ambrish Rawat AAML 13 297 0 21 Jul 2017
Fast Feature Fool: A data independent approach to universal adversarial perturbations Konda Reddy Mopuri Utsav Garg R. Venkatesh Babu AAML 36 205 0 18 Jul 2017
NO Need to Worry about Adversarial Examples in Object Detection in Autonomous Vehicles Jiajun Lu Hussein Sibai Evan Fabry David A. Forsyth AAML 17 280 0 12 Jul 2017
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks John Bradshaw A. G. Matthews Zoubin Ghahramani BDL AAML 72 171 0 08 Jul 2017
UPSET and ANGRI : Breaking High Performance Image Classifiers Sayantan Sarkar Ankan Bansal U. Mahbub Rama Chellappa AAML 30 108 0 04 Jul 2017
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks Shiyu Liang Yixuan Li R. Srikant UQCV OODD 32 2,031 0 08 Jun 2017
Robustness of classifiers to universal perturbations: a geometric perspective Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi Omar Fawzi P. Frossard Stefano Soatto AAML 29 118 0 26 May 2017
MagNet: a Two-Pronged Defense against Adversarial Examples Dongyu Meng Hao Chen AAML 13 1,198 0 25 May 2017
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation Matthias Hein Maksym Andriushchenko AAML 45 505 0 23 May 2017
MTDeep: Boosting the Security of Deep Neural Nets Against Adversarial Attacks with Moving Target Defense Sailik Sengupta Tathagata Chakraborti S. Kambhampati AAML 26 63 0 19 May 2017