v1v2 (latest)

The Space of Transferable Adversarial Examples

11 April 2017

Dan Boneh

Papers citing "The Space of Transferable Adversarial Examples"

50 / 302 papers shown

Title
Exploring Simple and Transferable Recognition-Aware Image Processing Zhuang Liu H. Wang Tinghui Zhou Zhiqiang Shen Bingyi Kang Evan Shelhamer Trevor Darrell 56 9 0 21 Oct 2019
Toward Metrics for Differentiating Out-of-Distribution Sets Mahdieh Abbasi Changjian Shui Arezoo Rajabi Christian Gagné R. Bobba OODD 30 4 0 18 Oct 2019
Man-in-the-Middle Attacks against Machine Learning Classifiers via Malicious Generative Models Derui Wang Wang Chaoran Li S. Wen Surya Nepal Yang Xiang AAML 34 35 0 14 Oct 2019
Learning deep forest with multi-scale Local Binary Pattern features for face anti-spoofing Rizhao Cai Changsheng Chen AAML CVBM 54 12 0 09 Oct 2019
GAMIN: An Adversarial Approach to Black-Box Model Inversion Ulrich Aïvodji Sébastien Gambs Timon Ther MLAU 73 42 0 26 Sep 2019
FENCE: Feasible Evasion Attacks on Neural Networks in Constrained Environments Alesia Chernikova Alina Oprea AAML 106 40 0 23 Sep 2019
HAWKEYE: Adversarial Example Detector for Deep Neural Networks Jinkyu Koo Michael A. Roth S. Bagchi AAML 232 3 0 22 Sep 2019
Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors Gilad Cohen Guillermo Sapiro Raja Giryes TDI 73 128 0 15 Sep 2019
Feedback Learning for Improving the Robustness of Neural Networks Chang Song Zuoguan Wang H. Li AAML 65 7 0 12 Sep 2019
Evaluating Defensive Distillation For Defending Text Processing Neural Networks Against Adversarial Examples Marcus Soll Tobias Hinz S. Magg S. Wermter AAML 48 22 0 21 Aug 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 110 231 0 24 Jul 2019
Understanding Adversarial Attacks on Deep Learning Based Medical Image Analysis Systems Xingjun Ma Yuhao Niu Lin Gu Yisen Wang Yitian Zhao James Bailey Feng Lu MedIm AAML 93 458 0 24 Jul 2019
Open DNN Box by Power Side-Channel Attack Yun Xiang Zhuangzhi Chen Zuohui Chen Zebin Fang Haiyang Hao Jinyin Chen Yi Liu Zhefu Wu Qi Xuan Xiaoniu Yang AAML 70 90 0 21 Jul 2019
Fooling a Real Car with Adversarial Traffic Signs N. Morgulis Alexander Kreines Shachar Mendelowitz Yuval Weisglass AAML 83 93 0 30 Jun 2019
Adversarial Robustness via Label-Smoothing Morgane Goibert Elvis Dohmatob AAML 124 18 0 27 Jun 2019
Beneficial perturbation network for continual learning Shixian Wen Laurent Itti CLL KELM 29 2 0 22 Jun 2019
Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang Tianyun Zhang Sijia Liu Pin-Yu Chen Jiacen Xu M. Fardad Yangqiu Song AAML 70 37 0 09 Jun 2019
Characterizing Bias in Classifiers using Generative Models Daniel J. McDuff Shuang Ma Yale Song Ashish Kapoor 92 47 0 30 May 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 89 191 0 29 May 2019
Snooping Attacks on Deep Reinforcement Learning Matthew J. Inkawhich Yiran Chen Hai Helen Li AAML 62 25 0 28 May 2019
Cross-Domain Transferability of Adversarial Perturbations Muzammal Naseer Salman H. Khan M. H. Khan Fahad Shahbaz Khan Fatih Porikli AAML 115 145 0 28 May 2019
Transferable Clean-Label Poisoning Attacks on Deep Neural Nets Chen Zhu Wenjie Huang Ali Shafahi Hengduo Li Gavin Taylor Christoph Studer Tom Goldstein 114 285 0 15 May 2019
Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas Shibani Santurkar Dimitris Tsipras Logan Engstrom Brandon Tran Aleksander Madry SILM 99 1,845 0 06 May 2019
NATTACK: Learning the Distributions of Adversarial Examples for an Improved Black-Box Attack on Deep Neural Networks Yandong Li Lijun Li Liqiang Wang Tong Zhang Boqing Gong AAML 84 245 0 01 May 2019
Analytical Moment Regularizer for Gaussian Robust Networks Modar Alfadly Adel Bibi Guohao Li AAML 29 4 0 24 Apr 2019
Reducing Adversarial Example Transferability Using Gradient Regularization George Adam P. Smirnov B. Haibe-Kains Anna Goldenberg AAML 81 4 0 16 Apr 2019
Cycle-Consistent Adversarial GAN: the integration of adversarial attack and defense Lingyun Jiang Kai Qiao Ruoxi Qin Linyuan Wang Jian Chen Haibing Bu Bin Yan AAML 32 8 0 12 Apr 2019
Malware Evasion Attack and Defense Yonghong Huang Utkarsh Verma Celeste Fralick G. Infante-Lopez B. Kumar Carl Woodward AAML 65 16 0 07 Apr 2019
Curls & Whey: Boosting Black-Box Adversarial Attacks Yucheng Shi Siyu Wang Yahong Han AAML 131 117 0 02 Apr 2019
Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks Aamir Mustafa Salman Khan Munawar Hayat Roland Göcke Jianbing Shen Ling Shao AAML 64 152 0 01 Apr 2019
On the Vulnerability of CNN Classifiers in EEG-Based BCIs Xiao Zhang Dongrui Wu AAML 73 82 0 31 Mar 2019
Generating Adversarial Examples With Conditional Generative Adversarial Net Ping Yu Kaitao Song Jianfeng Lu AAML GAN 43 23 0 18 Mar 2019
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples Kevin Roth Yannic Kilcher Thomas Hofmann AAML 80 176 0 13 Feb 2019
Robustness Certificates Against Adversarial Examples for ReLU Networks Sahil Singla Soheil Feizi AAML 68 21 0 01 Feb 2019
A New Family of Neural Networks Provably Resistant to Adversarial Attacks Rakshit Agrawal Luca de Alfaro D. Helmbold AAML OOD 39 2 0 01 Feb 2019
On the Effect of Low-Rank Weights on Adversarial Robustness of Neural Networks P. Langenberg E. Balda Arash Behboodi R. Mathar 50 16 0 29 Jan 2019
Improving Adversarial Robustness of Ensembles with Diversity Training Sanjay Kariyappa Moinuddin K. Qureshi AAML FedML 82 138 0 28 Jan 2019
Multi-Label Adversarial Perturbations Qingquan Song Haifeng Jin Xiao Huang Helen Zhou AAML 63 37 0 02 Jan 2019
A Multiversion Programming Inspired Approach to Detecting Audio Adversarial Examples Qiang Zeng Jianhai Su Chenglong Fu Golam Kayas Lannan Luo AAML 55 46 0 26 Dec 2018
Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial Attacks T. Brunner Frederik Diehl Michael Truong-Le Alois Knoll MLAU AAML 77 117 0 24 Dec 2018
AutoGAN: Robust Classifier Against Adversarial Attacks Blerta Lindqvist Shridatt Sugrim R. Izmailov AAML 38 7 0 08 Dec 2018
Adversarial Attacks for Optical Flow-Based Action Recognition Classifiers Nathan Inkawhich Matthew J. Inkawhich Yiran Chen H. Li AAML 43 38 0 28 Nov 2018
Intermediate Level Adversarial Attack for Enhanced Transferability Qian Huang Zeqi Gu Isay Katsman Horace He Pian Pawakapan Zhiqiu Lin Serge J. Belongie Ser-Nam Lim AAML SILM 54 4 0 20 Nov 2018
A Geometric Perspective on the Transferability of Adversarial Directions Duncan C. McElfresh H. Bidkhori Dimitris Papailiopoulos AAML 50 17 0 08 Nov 2018
Exploring Connections Between Active Learning and Model Extraction Varun Chandrasekaran Kamalika Chaudhuri Irene Giacomelli Shane Walker Songbai Yan MIACV 249 159 0 05 Nov 2018
Active Deep Learning Attacks under Strict Rate Limitations for Online API Calls Guofu Li Y. Sagduyu Kemal Davaslioglu Jason H. Li AAML 60 31 0 05 Nov 2018
The Faults in Our Pi Stars: Security Issues and Open Challenges in Deep Reinforcement Learning Vahid Behzadan Arslan Munir 80 27 0 23 Oct 2018
One Bit Matters: Understanding Adversarial Examples as the Abuse of Redundancy Jingkang Wang R. Jia Gerald Friedland Yangqiu Song C. Spanos AAML 32 4 0 23 Oct 2018
The Adversarial Attack and Detection under the Fisher Information Metric Chenxiao Zhao P. T. Fletcher Mixue Yu Chaomin Shen Guixu Zhang Yaxin Peng AAML 76 47 0 09 Oct 2018
Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel Attacks Sanghyun Hong Michael Davinroy Yigitcan Kaya S. Locke Ian Rackow Kevin Kulda Dana Dachman-Soled Tudor Dumitras MIACV 84 90 0 08 Oct 2018