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Towards Evaluating the Robustness of Neural Networks

16 August 2016

Papers citing "Towards Evaluating the Robustness of Neural Networks"

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Title
Model Compression with Adversarial Robustness: A Unified Optimization Framework Shupeng Gui Haotao Wang Chen Yu Haichuan Yang Zhangyang Wang Ji Liu MQ 81 139 0 10 Feb 2019
Daedalus: Breaking Non-Maximum Suppression in Object Detection via Adversarial Examples Derui Wang Chaoran Li S. Wen Qing-Long Han Surya Nepal Xiangyu Zhang Yang Xiang AAML 75 41 0 06 Feb 2019
Theoretical evidence for adversarial robustness through randomization Rafael Pinot Laurent Meunier Alexandre Araujo H. Kashima Florian Yger Cédric Gouy-Pailler Jamal Atif AAML 110 83 0 04 Feb 2019
Computational Limitations in Robust Classification and Win-Win Results Akshay Degwekar Preetum Nakkiran Vinod Vaikuntanathan 67 39 0 04 Feb 2019
Predictive Uncertainty Quantification with Compound Density Networks Agustinus Kristiadi Sina Daubener Asja Fischer BDL UQCV 83 17 0 04 Feb 2019
Collaborative Sampling in Generative Adversarial Networks Yuejiang Liu Parth Kothari Alexandre Alahi TTA 128 17 0 02 Feb 2019
Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation Sahil Singla Eric Wallace Shi Feng Soheil Feizi FAtt 71 60 0 01 Feb 2019
Robustness Certificates Against Adversarial Examples for ReLU Networks Sahil Singla Soheil Feizi AAML 68 21 0 01 Feb 2019
Adaptive Gradient for Adversarial Perturbations Generation Yatie Xiao Chi-Man Pun ODL 69 10 0 01 Feb 2019
Augmenting Model Robustness with Transformation-Invariant Attacks Houpu Yao Zhe Wang Guangyu Nie Yassine Mazboudi Yezhou Yang Yi Ren AAML OOD 31 3 0 31 Jan 2019
A Simple Explanation for the Existence of Adversarial Examples with Small Hamming Distance A. Shamir Itay Safran Eyal Ronen O. Dunkelman GAN AAML 59 95 0 30 Jan 2019
Who's Afraid of Adversarial Queries? The Impact of Image Modifications on Content-based Image Retrieval Zhuoran Liu Zhengyu Zhao Martha Larson AAML 79 43 0 29 Jan 2019
Improving Adversarial Robustness of Ensembles with Diversity Training Sanjay Kariyappa Moinuddin K. Qureshi AAML FedML 88 138 0 28 Jan 2019
Characterizing the Shape of Activation Space in Deep Neural Networks Thomas Gebhart Paul Schrater Alan Hylton AAML 72 7 0 28 Jan 2019
Weighted-Sampling Audio Adversarial Example Attack Xiaolei Liu Xiaosong Zhang Kun Wan Qingxin Zhu Yufei Ding DiffM AAML 51 36 0 26 Jan 2019
A Black-box Attack on Neural Networks Based on Swarm Evolutionary Algorithm Xiaolei Liu Yuheng Luo Xiaosong Zhang Qingxin Zhu AAML 58 16 0 26 Jan 2019
Improving Adversarial Robustness via Promoting Ensemble Diversity Tianyu Pang Kun Xu Chao Du Ning Chen Jun Zhu AAML 108 441 0 25 Jan 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 265 2,566 0 24 Jan 2019
Cross-Entropy Loss and Low-Rank Features Have Responsibility for Adversarial Examples Kamil Nar Orhan Ocal S. Shankar Sastry Kannan Ramchandran AAML 90 54 0 24 Jan 2019
Sensitivity Analysis of Deep Neural Networks Hai Shu Hongtu Zhu AAML 46 53 0 22 Jan 2019
Universal Rules for Fooling Deep Neural Networks based Text Classification Di Li Danilo Vasconcellos Vargas Kouichi Sakurai AAML 46 11 0 22 Jan 2019
Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey W. Zhang Quan Z. Sheng A. Alhazmi Chenliang Li AAML 125 57 0 21 Jan 2019
Optimization Problems for Machine Learning: A Survey Claudio Gambella Bissan Ghaddar Joe Naoum-Sawaya AI4CE 148 181 0 16 Jan 2019
The Limitations of Adversarial Training and the Blind-Spot Attack Huan Zhang Hongge Chen Zhao Song Duane S. Boning Inderjit S. Dhillon Cho-Jui Hsieh AAML 76 145 0 15 Jan 2019
Generating Adversarial Perturbation with Root Mean Square Gradient Yatie Xiao Chi-Man Pun Jizhe Zhou GAN 33 1 0 13 Jan 2019
ECGadv: Generating Adversarial Electrocardiogram to Misguide Arrhythmia Classification System Huangxun Chen Chenyu Huang Qianyi Huang Qian Zhang Wei Wang AAML 75 28 0 12 Jan 2019
Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries Christian Scano Battista Biggio Giovanni Lagorio Fabio Roli A. Armando AAML 80 131 0 11 Jan 2019
Characterizing and evaluating adversarial examples for Offline Handwritten Signature Verification L. G. Hafemann R. Sabourin Luiz Eduardo Soares de Oliveira AAML 55 44 0 10 Jan 2019
Extending Adversarial Attacks and Defenses to Deep 3D Point Cloud Classifiers Daniel Liu Ronald Yu Hao Su 3DPC 99 170 0 10 Jan 2019
Contamination Attacks and Mitigation in Multi-Party Machine Learning Jamie Hayes O. Ohrimenko AAML FedML 114 75 0 08 Jan 2019
Interpretable BoW Networks for Adversarial Example Detection Krishna Kanth Nakka Mathieu Salzmann GAN AAML 38 0 0 08 Jan 2019
Image Super-Resolution as a Defense Against Adversarial Attacks Aamir Mustafa Salman H. Khan Munawar Hayat Jianbing Shen Ling Shao AAML SupR 102 176 0 07 Jan 2019
Adversarial Examples Versus Cloud-based Detectors: A Black-box Empirical Study Xurong Li S. Ji Men Han Juntao Ji Zhenyu Ren Yushan Liu Chunming Wu AAML 96 31 0 04 Jan 2019
Adversarial CAPTCHAs Chenghui Shi Xiaogang Xu S. Ji Kai Bu Jianhai Chen R. Beyah Ting Wang AAML 51 53 0 04 Jan 2019
Multi-Label Adversarial Perturbations Qingquan Song Haifeng Jin Xiao Huang Helen Zhou AAML 63 37 0 02 Jan 2019
A Noise-Sensitivity-Analysis-Based Test Prioritization Technique for Deep Neural Networks Long Zhang Xuechao Sun Yong Li Zhenyu Zhang AAML 53 22 0 01 Jan 2019
Gray-box Adversarial Testing for Control Systems with Machine Learning Component Shakiba Yaghoubi Georgios Fainekos AAML 77 66 0 31 Dec 2018
Hessian-Aware Zeroth-Order Optimization for Black-Box Adversarial Attack Haishan Ye Zhichao Huang Cong Fang C. J. Li Tong Zhang AAML 87 42 0 29 Dec 2018
DeepBillboard: Systematic Physical-World Testing of Autonomous Driving Systems Husheng Zhou Wei Li Yuankun Zhu Yuqun Zhang Bei Yu Lingming Zhang Cong Liu AAML 85 180 0 27 Dec 2018
Adversarial Attack and Defense on Graph Data: A Survey Lichao Sun Yingtong Dou Carl Yang Ji Wang Yixin Liu Philip S. Yu Lifang He Yangqiu Song GNN AAML 139 287 0 26 Dec 2018
Seeing isn't Believing: Practical Adversarial Attack Against Object Detectors Yue Zhao Hong Zhu Ruigang Liang Qintao Shen Shengzhi Zhang Kai Chen AAML 65 15 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
Towards resilient machine learning for ransomware detection Li-Wei Chen Chih-Yuan Yang Anindya Paul R. Sahita AAML 36 22 0 21 Dec 2018
Enhancing Robustness of Deep Neural Networks Against Adversarial Malware Samples: Principles, Framework, and AICS'2019 Challenge Deqiang Li Qianmu Li Yanfang Ye Shouhuai Xu AAML 66 15 0 19 Dec 2018
A Survey of Safety and Trustworthiness of Deep Neural Networks: Verification, Testing, Adversarial Attack and Defence, and Interpretability Xiaowei Huang Daniel Kroening Wenjie Ruan Marta Kwiatkowska Youcheng Sun Emese Thamo Min Wu Xinping Yi AAML 132 51 0 18 Dec 2018
Spartan Networks: Self-Feature-Squeezing Neural Networks for increased robustness in adversarial settings François Menet Paul Berthier José M. Fernandez M. Gagnon AAML 27 10 0 17 Dec 2018
Defense-VAE: A Fast and Accurate Defense against Adversarial Attacks Xiang Li Shihao Ji AAML 75 26 0 17 Dec 2018
Perturbation Analysis of Learning Algorithms: A Unifying Perspective on Generation of Adversarial Examples E. Balda Arash Behboodi R. Mathar AAML 32 5 0 15 Dec 2018
Adversarial Sample Detection for Deep Neural Network through Model Mutation Testing Jingyi Wang Guoliang Dong Jun Sun Xinyu Wang Peixin Zhang AAML 80 191 0 14 Dec 2018
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 248 560 0 13 Dec 2018