Towards Evaluating the Robustness of Neural Networks

16 August 2016

Papers citing "Towards Evaluating the Robustness of Neural Networks"

50 / 1,604 papers shown

Title
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models Pouya Samangouei Maya Kabkab Rama Chellappa AAML GAN 29 1,166 0 17 May 2018
Gradient-Leaks: Understanding and Controlling Deanonymization in Federated Learning Tribhuvanesh Orekondy Seong Joon Oh Yang Zhang Bernt Schiele Mario Fritz PICV FedML 359 37 0 15 May 2018
Hu-Fu: Hardware and Software Collaborative Attack Framework against Neural Networks Wenshuo Li Jincheng Yu Xuefei Ning Pengjun Wang Qi Wei Yu Wang Huazhong Yang AAML 39 61 0 14 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
Curriculum Adversarial Training Qi-Zhi Cai Min Du Chang-rui Liu D. Song AAML 24 160 0 13 May 2018
Adversarially Robust Generalization Requires More Data Ludwig Schmidt Shibani Santurkar Dimitris Tsipras Kunal Talwar A. Madry OOD AAML 25 785 0 30 Apr 2018
Formal Security Analysis of Neural Networks using Symbolic Intervals Shiqi Wang Kexin Pei Justin Whitehouse Junfeng Yang Suman Jana AAML 25 473 0 28 Apr 2018
Towards Fast Computation of Certified Robustness for ReLU Networks Tsui-Wei Weng Huan Zhang Hongge Chen Zhao Song Cho-Jui Hsieh Duane S. Boning Inderjit S. Dhillon Luca Daniel AAML 38 686 0 25 Apr 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
Black-box Adversarial Attacks with Limited Queries and Information Andrew Ilyas Logan Engstrom Anish Athalye Jessy Lin MLAU AAML 46 1,190 0 23 Apr 2018
VectorDefense: Vectorization as a Defense to Adversarial Examples V. Kabilan Brandon L. Morris Anh Totti Nguyen AAML 22 21 0 23 Apr 2018
ADef: an Iterative Algorithm to Construct Adversarial Deformations Rima Alaifari Giovanni S. Alberti Tandri Gauksson AAML 19 96 0 20 Apr 2018
Semantic Adversarial Deep Learning S. Seshia S. Jha T. Dreossi AAML SILM 27 90 0 19 Apr 2018
ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector Shang-Tse Chen Cory Cornelius Jason Martin Duen Horng Chau ObjD 165 424 0 16 Apr 2018
Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the $L_0$ Norm Wenjie Ruan Min Wu Youcheng Sun Xiaowei Huang Daniel Kroening Marta Kwiatkowska AAML 11 38 0 16 Apr 2018
Adversarial Attacks Against Medical Deep Learning Systems S. G. Finlayson Hyung Won Chung I. Kohane Andrew L. Beam SILM AAML OOD MedIm 25 230 0 15 Apr 2018
An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks Pu Zhao Sijia Liu Yanzhi Wang X. Lin AAML 14 37 0 09 Apr 2018
The Effects of JPEG and JPEG2000 Compression on Attacks using Adversarial Examples Ayse Elvan Aydemir A. Temi̇zel T. Taşkaya-Temizel AAML 8 30 0 28 Mar 2018
Bypassing Feature Squeezing by Increasing Adversary Strength Yash Sharma Pin-Yu Chen AAML 11 34 0 27 Mar 2018
On the Limitation of Local Intrinsic Dimensionality for Characterizing the Subspaces of Adversarial Examples Pei-Hsuan Lu Pin-Yu Chen Chia-Mu Yu AAML 11 26 0 26 Mar 2018
An Overview of Vulnerabilities of Voice Controlled Systems Yuan Gong C. Poellabauer 19 32 0 24 Mar 2018
Understanding Measures of Uncertainty for Adversarial Example Detection Lewis Smith Y. Gal UQCV 52 358 0 22 Mar 2018
Adversarial Defense based on Structure-to-Signal Autoencoders Joachim Folz Sebastián M. Palacio Jörn Hees Damian Borth Andreas Dengel AAML 26 32 0 21 Mar 2018
Technical Report: When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks Octavian Suciu R. Marginean Yigitcan Kaya Hal Daumé Tudor Dumitras AAML 31 286 0 19 Mar 2018
Semantic Adversarial Examples Hossein Hosseini Radha Poovendran GAN AAML 31 196 0 16 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
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning Nicolas Papernot Patrick McDaniel OOD AAML 13 503 0 13 Mar 2018
Sparse Adversarial Perturbations for Videos Xingxing Wei Jun Zhu Hang Su AAML 14 138 0 07 Mar 2018
Protecting JPEG Images Against Adversarial Attacks Aaditya (Adi) Prakash N. Moran Solomon Garber Antonella DiLillo J. Storer AAML 23 34 0 02 Mar 2018
Understanding and Enhancing the Transferability of Adversarial Examples Lei Wu Zhanxing Zhu Cheng Tai E. Weinan AAML SILM 30 96 0 27 Feb 2018
Robust GANs against Dishonest Adversaries Zhi Xu Chengtao Li Stefanie Jegelka AAML 34 3 0 27 Feb 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
Verifying Controllers Against Adversarial Examples with Bayesian Optimization Shromona Ghosh Felix Berkenkamp G. Ranade S. Qadeer Ashish Kapoor AAML 33 45 0 23 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 21 165 0 22 Feb 2018
L2-Nonexpansive Neural Networks Haifeng Qian M. Wegman 25 74 0 22 Feb 2018
Generalizable Adversarial Examples Detection Based on Bi-model Decision Mismatch João Monteiro Isabela Albuquerque Zahid Akhtar T. Falk AAML 41 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 43 225 0 19 Feb 2018
Are Generative Classifiers More Robust to Adversarial Attacks? Yingzhen Li John Bradshaw Yash Sharma AAML 57 78 0 19 Feb 2018
Stealing Hyperparameters in Machine Learning Binghui Wang Neil Zhenqiang Gong AAML 45 458 0 14 Feb 2018
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach Tsui-Wei Weng Huan Zhang Pin-Yu Chen Jinfeng Yi D. Su Yupeng Gao Cho-Jui Hsieh Luca Daniel AAML 25 463 0 31 Jan 2018
Adversarial Texts with Gradient Methods Zhitao Gong Wenlu Wang Yangqiu Song D. Song Wei-Shinn Ku AAML 34 77 0 22 Jan 2018
Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers Ji Gao Jack Lanchantin M. Soffa Yanjun Qi AAML 47 707 0 13 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-wen Li Yisen Wang S. Erfani S. Wijewickrema Grant Schoenebeck D. Song Michael E. Houle James Bailey AAML 40 728 0 08 Jan 2018
Deep Fingerprinting: Undermining Website Fingerprinting Defenses with Deep Learning Payap Sirinam Mohsen Imani Marc Juárez M. Wright 19 453 0 07 Jan 2018
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text Nicholas Carlini D. Wagner AAML 38 1,074 0 05 Jan 2018
Did you hear that? Adversarial Examples Against Automatic Speech Recognition M. Alzantot Bharathan Balaji Mani B. Srivastava AAML 18 251 0 02 Jan 2018