On Detecting Adversarial Perturbations

14 February 2017

Papers citing "On Detecting Adversarial Perturbations"

38 / 188 papers shown

Title
Detection based Defense against Adversarial Examples from the Steganalysis Point of View Jiayang Liu Weiming Zhang Yiwei Zhang Dongdong Hou Yujia Liu Hongyue Zha Nenghai Yu AAML 25 99 0 21 Jun 2018
Bidirectional Learning for Robust Neural Networks S. Pontes-Filho Marcus Liwicki 29 9 0 21 May 2018
Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing Jingyi Wang Jun Sun Peixin Zhang Xinyu Wang AAML 21 41 0 14 May 2018
AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning Jinyuan Jia Neil Zhenqiang Gong AAML 13 161 0 13 May 2018
Towards Dependable Deep Convolutional Neural Networks (CNNs) with Out-distribution Learning Mahdieh Abbasi Arezoo Rajabi Christian Gagné R. Bobba OODD 30 6 0 24 Apr 2018
Clipping free attacks against artificial neural networks B. Addad Jérôme Kodjabachian Christophe Meyer AAML 19 1 0 26 Mar 2018
Defending against Adversarial Attack towards Deep Neural Networks via Collaborative Multi-task Training Derui Wang Chaoran Li S. Wen Surya Nepal Yang Xiang AAML 41 29 0 14 Mar 2018
Rethinking Feature Distribution for Loss Functions in Image Classification Weitao Wan Yuanyi Zhong Tianpeng Li Jiansheng Chen 21 166 0 08 Mar 2018
On the Suitability of $L_p$ -norms for Creating and Preventing Adversarial Examples Mahmood Sharif Lujo Bauer Michael K. Reiter AAML 24 138 0 27 Feb 2018
Deep Defense: Training DNNs with Improved Adversarial Robustness Ziang Yan Yiwen Guo Changshui Zhang AAML 38 109 0 23 Feb 2018
Unravelling Robustness of Deep Learning based Face Recognition Against Adversarial Attacks Gaurav Goswami Nalini Ratha Akshay Agarwal Richa Singh Mayank Vatsa AAML 26 165 0 22 Feb 2018
Generalizable Adversarial Examples Detection Based on Bi-model Decision Mismatch João Monteiro Isabela Albuquerque Zahid Akhtar T. Falk AAML 46 29 0 21 Feb 2018
On Lyapunov exponents and adversarial perturbation Vinay Uday Prabhu Nishant Desai John Whaley AAML 20 4 0 20 Feb 2018
Shield: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression Nilaksh Das Madhuri Shanbhogue Shang-Tse Chen Fred Hohman Siwei Li Li-Wei Chen Michael E. Kounavis Duen Horng Chau FedML AAML 45 225 0 19 Feb 2018
A3T: Adversarially Augmented Adversarial Training Akram Erraqabi A. Baratin Yoshua Bengio Simon Lacoste-Julien AAML 38 9 0 12 Jan 2018
Less is More: Culling the Training Set to Improve Robustness of Deep Neural Networks Yongshuai Liu Jiyu Chen Hao Chen AAML 27 14 0 09 Jan 2018
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality Xingjun Ma Bo Li Yisen Wang S. Erfani S. Wijewickrema Grant Schoenebeck D. Song Michael E. Houle James Bailey AAML 43 730 0 08 Jan 2018
A General Framework for Adversarial Examples with Objectives Mahmood Sharif Sruti Bhagavatula Lujo Bauer Michael K. Reiter AAML GAN 13 191 0 31 Dec 2017
ReabsNet: Detecting and Revising Adversarial Examples Jiefeng Chen Zihang Meng Changtian Sun Weiliang Tang Yinglun Zhu AAML GAN 29 4 0 21 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
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
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
Detecting Adversarial Attacks on Neural Network Policies with Visual Foresight Yen-Chen Lin Ming Liu Min Sun Jia-Bin Huang AAML 29 48 0 02 Oct 2017
Provably Minimally-Distorted Adversarial Examples Nicholas Carlini Guy Katz Clark W. Barrett D. Dill AAML 33 89 0 29 Sep 2017
Ensemble Methods as a Defense to Adversarial Perturbations Against Deep Neural Networks Thilo Strauss Markus Hanselmann Andrej Junginger Holger Ulmer AAML 34 134 0 11 Sep 2017
Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong Warren He James Wei Xinyun Chen Nicholas Carlini D. Song AAML 43 242 0 15 Jun 2017
Classification regions of deep neural networks Alhussein Fawzi Seyed-Mohsen Moosavi-Dezfooli P. Frossard Stefano Soatto 31 51 0 26 May 2017
MagNet: a Two-Pronged Defense against Adversarial Examples Dongyu Meng Hao Chen AAML 13 1,199 0 25 May 2017
Detecting Adversarial Image Examples in Deep Networks with Adaptive Noise Reduction Bin Liang Hongcheng Li Miaoqiang Su Xirong Li Wenchang Shi Xiaofeng Wang AAML 14 216 0 23 May 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 61 1,842 0 20 May 2017
DeepXplore: Automated Whitebox Testing of Deep Learning Systems Kexin Pei Yinzhi Cao Junfeng Yang Suman Jana AAML 48 1,353 0 18 May 2017
Extending Defensive Distillation Nicolas Papernot Patrick McDaniel AAML 32 118 0 15 May 2017
Universal Adversarial Perturbations Against Semantic Image Segmentation J. H. Metzen Mummadi Chaithanya Kumar Thomas Brox Volker Fischer AAML 30 287 0 19 Apr 2017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks Weilin Xu David Evans Yanjun Qi AAML 25 1,237 0 04 Apr 2017
Blocking Transferability of Adversarial Examples in Black-Box Learning Systems Hossein Hosseini Yize Chen Sreeram Kannan Baosen Zhang Radha Poovendran AAML 30 106 0 13 Mar 2017
Detecting Adversarial Samples from Artifacts Reuben Feinman Ryan R. Curtin S. Shintre Andrew B. Gardner AAML 36 886 0 01 Mar 2017
On the (Statistical) Detection of Adversarial Examples Kathrin Grosse Praveen Manoharan Nicolas Papernot Michael Backes Patrick McDaniel AAML 39 709 0 21 Feb 2017
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 353 5,849 0 08 Jul 2016