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Towards Deep Learning Models Resistant to Adversarial Attacks

19 June 2017

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

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Title
Truth or Backpropaganda? An Empirical Investigation of Deep Learning TheoryInternational Conference on Learning Representations (ICLR), 2019 Micah Goldblum Jonas Geiping Avi Schwarzschild Michael Moeller Tom Goldstein 415 36 0 01 Oct 2019
Predicting with High Correlation Features Devansh Arpit Caiming Xiong R. Socher OODD OOD 161 7 0 01 Oct 2019
Role of Spatial Context in Adversarial Robustness for Object Detection Aniruddha Saha Akshayvarun Subramanya Koninika Patil Hamed Pirsiavash ObjD AAML 440 59 0 30 Sep 2019
Synthesizing Action Sequences for Modifying Model DecisionsAAAI Conference on Artificial Intelligence (AAAI), 2019 Goutham Ramakrishnan Yun Chan Lee Aws Albarghouthi 334 37 0 30 Sep 2019
Hidden Trigger Backdoor AttacksAAAI Conference on Artificial Intelligence (AAAI), 2019 Aniruddha Saha Akshayvarun Subramanya Hamed Pirsiavash 442 686 0 30 Sep 2019
Black-box Adversarial Attacks with Bayesian Optimization Satya Narayan Shukla Anit Kumar Sahu Devin Willmott J. Zico Kolter AAML MLAU 124 33 0 30 Sep 2019
Min-Max Optimization without Gradients: Convergence and Applications to Adversarial ML Sijia Liu Songtao Lu Xiangyi Chen Yao Feng Kaidi Xu Abdullah Al-Dujaili Mingyi Hong Una-May Obelilly 276 26 0 30 Sep 2019
Deep k-NN Defense against Clean-label Data Poisoning Attacks Neehar Peri Neal Gupta Wenjie Huang Liam H. Fowl Chen Zhu Soheil Feizi Tom Goldstein John P. Dickerson AAML 181 7 0 29 Sep 2019
Library network, a possible path to explainable neural networks J. H. Lee AAML AI4CE 128 0 0 29 Sep 2019
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts Yu Sun Xiaolong Wang Zhuang Liu John Miller Alexei A. Efros Moritz Hardt TTA OOD 271 104 0 29 Sep 2019
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural NetworksInternational Conference on Cyberworlds (ICC), 2019 Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 203 18 0 27 Sep 2019
Lower Bounds on Adversarial Robustness from Optimal TransportNeural Information Processing Systems (NeurIPS), 2019 A. Bhagoji Daniel Cullina Prateek Mittal OOD OT AAML 168 97 0 26 Sep 2019
Towards neural networks that provably know when they don't knowInternational Conference on Learning Representations (ICLR), 2019 Alexander Meinke Matthias Hein OODD 232 147 0 26 Sep 2019
Towards Explainable Artificial Intelligence Wojciech Samek K. Müller XAI 213 489 0 26 Sep 2019
FreeLB: Enhanced Adversarial Training for Natural Language UnderstandingInternational Conference on Learning Representations (ICLR), 2019 Chen Zhu Yu Cheng Zhe Gan S. Sun Tom Goldstein Jingjing Liu AAML 616 487 0 25 Sep 2019
Mixup Inference: Better Exploiting Mixup to Defend Adversarial AttacksInternational Conference on Learning Representations (ICLR), 2019 Tianyu Pang Kun Xu Jun Zhu AAML 187 111 0 25 Sep 2019
Sign-OPT: A Query-Efficient Hard-label Adversarial AttackInternational Conference on Learning Representations (ICLR), 2019 Minhao Cheng Simranjit Singh Patrick H. Chen Pin-Yu Chen Sijia Liu Cho-Jui Hsieh AAML 500 244 0 24 Sep 2019
MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial ExamplesConference on Computer and Communications Security (CCS), 2019 Jinyuan Jia Ahmed Salem Michael Backes Yang Zhang Neil Zhenqiang Gong 261 433 0 23 Sep 2019
FENCE: Feasible Evasion Attacks on Neural Networks in Constrained EnvironmentsACM Transactions on Privacy and Security (TOPS), 2019 Alesia Chernikova Alina Oprea AAML 425 47 0 23 Sep 2019
Robust Local Features for Improving the Generalization of Adversarial TrainingInternational Conference on Learning Representations (ICLR), 2019 Chuanbiao Song Kun He Jiadong Lin Liwei Wang John E. Hopcroft OOD AAML 277 76 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 124 30 0 20 Sep 2019
Defending Against Physically Realizable Attacks on Image ClassificationInternational Conference on Learning Representations (ICLR), 2019 Tong Wu Liang Tong Yevgeniy Vorobeychik AAML 238 140 0 20 Sep 2019
Representation Learning for Electronic Health Records W. Weng Peter Szolovits 150 20 0 19 Sep 2019
Training Robust Deep Neural Networks via Adversarial Noise PropagationIEEE Transactions on Image Processing (TIP), 2019 Aishan Liu Xianglong Liu Chongzhi Zhang Hang Yu Qiang Liu Dacheng Tao AAML 106 132 0 19 Sep 2019
Adversarial Vulnerability Bounds for Gaussian Process ClassificationMachine-mediated learning (ML), 2019 M. Smith Kathrin Grosse Michael Backes Mauricio A. Alvarez AAML 103 9 0 19 Sep 2019
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural NetworksAAAI Conference on Artificial Intelligence (AAAI), 2019 Sekitoshi Kanai Yasutoshi Ida Yasuhiro Fujiwara Masanori Yamada S. Adachi AAML 137 1 0 19 Sep 2019
Adversarial Attacks and Defenses in Images, Graphs and Text: A ReviewInternational Journal of Automation and Computing (IJAC), 2019 Han Xu Yao Ma Haochen Liu Debayan Deb Hui Liu Shucheng Zhou Anil K. Jain AAML 287 725 0 17 Sep 2019
Towards Quality Assurance of Software Product Lines with Adversarial ConfigurationsSoftware Product Lines Conference (SPLC), 2019 Paul Temple M. Acher Gilles Perrouin Battista Biggio J. Jézéquel Fabio Roli AAML 67 12 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 298 19 0 16 Sep 2019
Detecting Adversarial Samples Using Influence Functions and Nearest NeighborsComputer Vision and Pattern Recognition (CVPR), 2019 Gilad Cohen Guillermo Sapiro Raja Giryes TDI 200 135 0 15 Sep 2019
White-Box Adversarial Defense via Self-Supervised Data Estimation Zudi Lin Hanspeter Pfister Ziming Zhang AAML 130 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 119 13 0 13 Sep 2019
Towards Model-Agnostic Adversarial Defenses using Adversarially Trained Autoencoders Pratik Vaishnavi Kevin Eykholt A. Prakash Amir Rahmati AAML 165 2 0 12 Sep 2019
Inspecting adversarial examples using the Fisher information Jörg Martin Clemens Elster AAML 91 15 0 12 Sep 2019
Feedback Learning for Improving the Robustness of Neural NetworksInternational Conference on Machine Learning and Applications (ICMLA), 2019 Chang Song Zuoguan Wang Xue Yang AAML 93 8 0 12 Sep 2019
Structural Robustness for Deep Learning ArchitecturesData Science Workshop (DS), 2019 Carlos Lassance Vincent Gripon Jian Tang Antonio Ortega OOD 127 3 0 11 Sep 2019
Sparse and Imperceivable Adversarial AttacksIEEE International Conference on Computer Vision (ICCV), 2019 Francesco Croce Matthias Hein AAML 194 218 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 147 12 0 11 Sep 2019
Localized Adversarial Training for Increased Accuracy and Robustness in Image Classification Eitan Rothberg Tingting Chen Luo Jie Hao Ji AAML 54 0 0 10 Sep 2019
Neural Belief ReasonerInternational Joint Conference on Artificial Intelligence (IJCAI), 2019 Haifeng Qian NAI BDL 124 1 0 10 Sep 2019
FDA: Feature Disruptive AttackIEEE International Conference on Computer Vision (ICCV), 2019 Aditya Ganeshan S. VivekB. R. Venkatesh Babu AAML 214 129 0 10 Sep 2019
TBT: Targeted Neural Network Attack with Bit TrojanComputer Vision and Pattern Recognition (CVPR), 2019 Adnan Siraj Rakin Zhezhi He Deliang Fan AAML 237 241 0 10 Sep 2019
Learning to Disentangle Robust and Vulnerable Features for Adversarial Detection Byunggill Joe Sung Ju Hwang I. Shin AAML 81 2 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 184 1 0 10 Sep 2019
Improving the Explainability of Neural Sentiment Classifiers via Data Augmentation Hanjie Chen Yangfeng Ji 247 11 0 10 Sep 2019
Adversarial Robustness Against the Union of Multiple Perturbation ModelsInternational Conference on Machine Learning (ICML), 2019 Pratyush Maini Eric Wong J. Zico Kolter OOD AAML 233 163 0 09 Sep 2019
When Explainability Meets Adversarial Learning: Detecting Adversarial Examples using SHAP SignaturesIEEE International Joint Conference on Neural Network (IJCNN), 2019 Gil Fidel Ron Bitton A. Shabtai FAtt GAN 127 130 0 08 Sep 2019
On the Need for Topology-Aware Generative Models for Manifold-Based DefensesInternational Conference on Learning Representations (ICLR), 2019 Uyeong Jang Susmit Jha S. Jha AAML 248 14 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 187 34 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 107 2 0 06 Sep 2019