Towards Deep Learning Models Resistant to Adversarial Attacks

19 June 2017

Papers citing "Towards Deep Learning Models Resistant to Adversarial Attacks"

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Title
Robust Local Features for Improving the Generalization of Adversarial Training Chuanbiao Song Kun He Jiadong Lin Liwei Wang J. Hopcroft OOD AAML 14 68 0 23 Sep 2019
COPYCAT: Practical Adversarial Attacks on Visualization-Based Malware Detection Aminollah Khormali Ahmed A. Abusnaina Songqing Chen Daehun Nyang Aziz Mohaisen AAML 34 28 0 20 Sep 2019
Defending Against Physically Realizable Attacks on Image Classification Tong Wu Liang Tong Yevgeniy Vorobeychik AAML 25 125 0 20 Sep 2019
Representation Learning for Electronic Health Records W. Weng Peter Szolovits 36 19 0 19 Sep 2019
Training Robust Deep Neural Networks via Adversarial Noise Propagation Aishan Liu Xianglong Liu Chongzhi Zhang Hang Yu Qiang Liu Dacheng Tao AAML 27 110 0 19 Sep 2019
Adversarial Vulnerability Bounds for Gaussian Process Classification M. Smith Kathrin Grosse Michael Backes Mauricio A. Alvarez AAML 16 9 0 19 Sep 2019
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks Sekitoshi Kanai Yasutoshi Ida Yasuhiro Fujiwara Masanori Yamada S. Adachi AAML 23 1 0 19 Sep 2019
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review Han Xu Yao Ma Haochen Liu Debayan Deb Hui Liu Jiliang Tang Anil K. Jain AAML 39 669 0 17 Sep 2019
Towards Quality Assurance of Software Product Lines with Adversarial Configurations Paul Temple M. Acher Gilles Perrouin Battista Biggio J. Jézéquel Fabio Roli AAML 22 11 0 16 Sep 2019
Interpreting and Improving Adversarial Robustness of Deep Neural Networks with Neuron Sensitivity Chongzhi Zhang Aishan Liu Xianglong Liu Yitao Xu Hang Yu Yuqing Ma Tianlin Li AAML 27 19 0 16 Sep 2019
Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors Gilad Cohen Guillermo Sapiro Raja Giryes TDI 19 124 0 15 Sep 2019
White-Box Adversarial Defense via Self-Supervised Data Estimation Zudi Lin Hanspeter Pfister Ziming Zhang AAML 16 2 0 13 Sep 2019
Defending Against Adversarial Attacks by Suppressing the Largest Eigenvalue of Fisher Information Matrix Yaxin Peng Chaomin Shen Guixu Zhang Jinsong Fan AAML 14 13 0 13 Sep 2019
Towards Model-Agnostic Adversarial Defenses using Adversarially Trained Autoencoders Pratik Vaishnavi Kevin Eykholt A. Prakash Amir Rahmati AAML 28 2 0 12 Sep 2019
Inspecting adversarial examples using the Fisher information Jörg Martin Clemens Elster AAML 23 15 0 12 Sep 2019
Feedback Learning for Improving the Robustness of Neural Networks Chang Song Zuoguan Wang H. Li AAML 39 7 0 12 Sep 2019
Structural Robustness for Deep Learning Architectures Carlos Lassance Vincent Gripon Jian Tang Antonio Ortega OOD 30 2 0 11 Sep 2019
Sparse and Imperceivable Adversarial Attacks Francesco Croce Matthias Hein AAML 39 199 0 11 Sep 2019
PDA: Progressive Data Augmentation for General Robustness of Deep Neural Networks Hang Yu Aishan Liu Xianglong Liu Gen Li Ping Luo R. Cheng Jichen Yang Chongzhi Zhang AAML 34 10 0 11 Sep 2019
Localized Adversarial Training for Increased Accuracy and Robustness in Image Classification Eitan Rothberg Tingting Chen Luo Jie Hao Ji AAML 8 0 0 10 Sep 2019
Neural Belief Reasoner Haifeng Qian NAI BDL 24 1 0 10 Sep 2019
FDA: Feature Disruptive Attack Aditya Ganeshan S. VivekB. R. Venkatesh Babu AAML 34 100 0 10 Sep 2019
TBT: Targeted Neural Network Attack with Bit Trojan Adnan Siraj Rakin Zhezhi He Deliang Fan AAML 24 211 0 10 Sep 2019
Learning to Disentangle Robust and Vulnerable Features for Adversarial Detection Byunggill Joe Sung Ju Hwang I. Shin AAML 16 1 0 10 Sep 2019
BOSH: An Efficient Meta Algorithm for Decision-based Attacks Zhenxin Xiao Puyudi Yang Yuchen Eleanor Jiang Kai-Wei Chang Cho-Jui Hsieh AAML 24 1 0 10 Sep 2019
Improving the Explainability of Neural Sentiment Classifiers via Data Augmentation Hanjie Chen Yangfeng Ji 19 9 0 10 Sep 2019
Adversarial Robustness Against the Union of Multiple Perturbation Models Pratyush Maini Eric Wong J. Zico Kolter OOD AAML 26 150 0 09 Sep 2019
When Explainability Meets Adversarial Learning: Detecting Adversarial Examples using SHAP Signatures Gil Fidel Ron Bitton A. Shabtai FAtt GAN 21 119 0 08 Sep 2019
On the Need for Topology-Aware Generative Models for Manifold-Based Defenses Uyeong Jang Susmit Jha S. Jha AAML 33 13 0 07 Sep 2019
Blackbox Attacks on Reinforcement Learning Agents Using Approximated Temporal Information Yiren Zhao Ilia Shumailov Han Cui Xitong Gao Robert D. Mullins Ross J. Anderson AAML 9 28 0 06 Sep 2019
Natural Adversarial Sentence Generation with Gradient-based Perturbation Yu-Lun Hsieh Minhao Cheng Da-Cheng Juan Wei Wei W. Hsu Cho-Jui Hsieh AAML 15 2 0 06 Sep 2019
Are Adversarial Robustness and Common Perturbation Robustness Independent Attributes ? Alfred Laugros A. Caplier Matthieu Ospici AAML 22 40 0 04 Sep 2019
Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation Po-Sen Huang Robert Stanforth Johannes Welbl Chris Dyer Dani Yogatama Sven Gowal Krishnamurthy Dvijotham Pushmeet Kohli AAML 22 164 0 03 Sep 2019
High Accuracy and High Fidelity Extraction of Neural Networks Matthew Jagielski Nicholas Carlini David Berthelot Alexey Kurakin Nicolas Papernot MLAU MIACV 45 372 0 03 Sep 2019
Certified Robustness to Adversarial Word Substitutions Robin Jia Aditi Raghunathan Kerem Göksel Percy Liang AAML 194 291 0 03 Sep 2019
Metric Learning for Adversarial Robustness Chengzhi Mao Ziyuan Zhong Junfeng Yang Carl Vondrick Baishakhi Ray OOD 27 184 0 03 Sep 2019
Defeating Misclassification Attacks Against Transfer Learning Bang Wu Shuo Wang Xingliang Yuan Cong Wang Carsten Rudolph Xiangwen Yang AAML 24 6 0 29 Aug 2019
Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness Ling Liu Wenqi Wei Ka-Ho Chow Margaret Loper Emre Gursoy Stacey Truex Yanzhao Wu UQCV AAML FedML 21 59 0 29 Aug 2019
Adversarial Edit Attacks for Tree Data Benjamin Paassen AAML 11 0 0 25 Aug 2019
Improving Adversarial Robustness via Attention and Adversarial Logit Pairing Dou Goodman Xingjian Li Ji Liu Jun Huan Tao Wei AAML 16 7 0 23 Aug 2019
AdvHat: Real-world adversarial attack on ArcFace Face ID system Stepan Alekseevich Komkov Aleksandr Petiushko AAML CVBM 16 283 0 23 Aug 2019
Testing Robustness Against Unforeseen Adversaries Maximilian Kaufmann Daniel Kang Yi Sun Steven Basart Xuwang Yin ... Adam Dziedzic Franziska Boenisch Tom B. Brown Jacob Steinhardt Dan Hendrycks AAML 17 0 0 21 Aug 2019
Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks Ka-Ho Chow Wenqi Wei Yanzhao Wu Ling Liu AAML 25 15 0 21 Aug 2019
Saccader: Improving Accuracy of Hard Attention Models for Vision Gamaleldin F. Elsayed Simon Kornblith Quoc V. Le VLM 29 72 0 20 Aug 2019
Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses Tianlin Li Siyue Wang Pin-Yu Chen Yanzhi Wang Brian Kulis Xue Lin S. Chin AAML 16 42 0 20 Aug 2019
Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries Fnu Suya Jianfeng Chi David Evans Yuan Tian AAML 22 85 0 19 Aug 2019
Adversarial Defense by Suppressing High-frequency Components Zhendong Zhang Cheolkon Jung X. Liang 12 24 0 19 Aug 2019
SPOCC: Scalable POssibilistic Classifier Combination -- toward robust aggregation of classifiers Mahmoud Albardan John Klein O. Colot 13 5 0 18 Aug 2019
Implicit Deep Learning L. Ghaoui Fangda Gu Bertrand Travacca Armin Askari Alicia Y. Tsai AI4CE 39 176 0 17 Aug 2019
Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks Jiadong Lin Chuanbiao Song Kun He Liwei Wang J. Hopcroft AAML 38 555 0 17 Aug 2019