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Provable defenses against adversarial examples via the convex outer adversarial polytope

2 November 2017

Eric Wong

J. Zico Kolter

AAML

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Papers citing "Provable defenses against adversarial examples via the convex outer adversarial polytope"

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Title
Data-Driven Certification of Neural Networks with Random Input NoiseIEEE Transactions on Control of Network Systems (TCNS), 2020 Brendon G. Anderson Somayeh Sojoudi AAML 339 12 0 02 Oct 2020
Block-wise Image Transformation with Secret Key for Adversarially Robust DefenseIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2020 Maungmaung Aprilpyone Hitoshi Kiya 136 58 0 02 Oct 2020
Bag of Tricks for Adversarial TrainingInternational Conference on Learning Representations (ICLR), 2020 Tianyu Pang Xiao Yang Yinpeng Dong Hang Su Jun Zhu AAML 329 282 0 01 Oct 2020
Assessing Robustness of Text Classification through Maximal Safe Radius ComputationFindings (Findings), 2020 Emanuele La Malfa Min Wu Luca Laurenti Benjie Wang Anthony Hartshorn Marta Z. Kwiatkowska AAML 188 19 0 01 Oct 2020
Adversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated GradientsMathematical and Scientific Machine Learning (MSML), 2020 Yifei Huang Yaodong Yu Hongyang R. Zhang Yi-An Ma Xingtai Lv AAML 146 30 0 28 Sep 2020
Semantics-Preserving Adversarial Training Won-Ok Lee Hanbit Lee Sang-goo Lee AAML 116 2 0 23 Sep 2020
NeuroDiff: Scalable Differential Verification of Neural Networks using Fine-Grained ApproximationInternational Conference on Automated Software Engineering (ASE), 2020 Brandon Paulsen Jingbo Wang Jiawei Wang Chao Wang 170 40 0 21 Sep 2020
Efficient Certification of Spatial RobustnessAAAI Conference on Artificial Intelligence (AAAI), 2020 Anian Ruoss Maximilian Baader Mislav Balunović Martin Vechev AAML 131 26 0 19 Sep 2020
EI-MTD:Moving Target Defense for Edge Intelligence against Adversarial AttacksACM Transactions on Privacy and Security (TOPS), 2020 Yaguan Qian Qiqi Shao Jiamin Wang Xiangyuan Lin Yankai Guo Zhaoquan Gu Bin Wang Chunming Wu AAML 253 26 0 19 Sep 2020
Deep Learning & Software Engineering: State of Research and Future Directions P. Devanbu Matthew B. Dwyer Sebastian G. Elbaum M. Lowry Kevin Moran Denys Poshyvanyk Baishakhi Ray Rishabh Singh Xiangyu Zhang 116 23 0 17 Sep 2020
Large Norms of CNN Layers Do Not Hurt Adversarial RobustnessAAAI Conference on Artificial Intelligence (AAAI), 2020 Youwei Liang Dong Huang 302 12 0 17 Sep 2020
Certifying Confidence via Randomized SmoothingNeural Information Processing Systems (NeurIPS), 2020 Aounon Kumar Alexander Levine Soheil Feizi Tom Goldstein UQCV 215 41 0 17 Sep 2020
A Game Theoretic Analysis of Additive Adversarial Attacks and DefensesNeural Information Processing Systems (NeurIPS), 2020 Ambar Pal René Vidal AAML 194 30 0 14 Sep 2020
Towards the Quantification of Safety Risks in Deep Neural Networks Peipei Xu Wenjie Ruan Xiaowei Huang 155 7 0 13 Sep 2020
Defending Against Multiple and Unforeseen Adversarial VideosIEEE Transactions on Image Processing (TIP), 2020 Shao-Yuan Lo Vishal M. Patel AAML 320 28 0 11 Sep 2020
SoK: Certified Robustness for Deep Neural NetworksIEEE Symposium on Security and Privacy (IEEE S&P), 2020 Linyi Li Tao Xie Yue Liu AAML 592 143 0 09 Sep 2020
Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial AttacksNeural Information Processing Systems (NeurIPS), 2020 Wei-An Lin Chun Pong Lau Alexander Levine Ramalingam Chellappa Soheil Feizi AAML 212 63 0 05 Sep 2020
Benchmarking adversarial attacks and defenses for time-series dataInternational Conference on Neural Information Processing (ICONIP), 2020 Shoaib Ahmed Siddiqui Andreas Dengel Sheraz Ahmed AAML AI4TS 113 15 0 30 Aug 2020
Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and MoreInternational Conference on Machine Learning (ICML), 2020 Aleksandar Bojchevski Johannes Klicpera Stephan Günnemann AAML 278 93 0 29 Aug 2020
Adversarially Robust Learning via Entropic RegularizationFrontiers in Artificial Intelligence (FAI), 2020 Gauri Jagatap Ameya Joshi A. B. Chowdhury S. Garg Chinmay Hegde OOD 223 12 0 27 Aug 2020
$On $\ell_p$-norm Robustness of Ensemble Stumps and Trees$ On $\ell_p$ -norm Robustness of Ensemble Stumps and Trees Yihan Wang Huan Zhang Hongge Chen Duane S. Boning Cho-Jui Hsieh AAML 160 7 0 20 Aug 2020
Improving adversarial robustness of deep neural networks by using semantic information Lina Wang Rui Tang Yawei Yue Xingshu Chen Wei Wang Yi Zhu Xuemei Zeng AAML 197 17 0 18 Aug 2020
Adversarial Training and Provable Robustness: A Tale of Two Objectives Jiameng Fan Wenchao Li AAML 201 23 0 13 Aug 2020
Learning to Learn from Mistakes: Robust Optimization for Adversarial NoiseInternational Conference on Artificial Neural Networks (ICANN), 2020 A. Serban E. Poll Joost Visser AAML 155 1 0 12 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive SurveyACM Computing Surveys (ACM CSUR), 2020 A. Serban E. Poll Joost Visser AAML 389 79 0 07 Aug 2020
Stronger and Faster Wasserstein Adversarial AttacksInternational Conference on Machine Learning (ICML), 2020 Kaiwen Wu Allen Wang Yaoliang Yu AAML 153 38 0 06 Aug 2020
Robust Deep Reinforcement Learning through Adversarial Loss Tuomas P. Oikarinen Wang Zhang Alexandre Megretski Luca Daniel Tsui-Wei Weng AAML 319 114 0 05 Aug 2020
Efficient Adversarial Attacks for Visual Object TrackingEuropean Conference on Computer Vision (ECCV), 2020 Yaning Tan Xingxing Wei Siyuan Yao Xiaochun Cao AAML 179 93 0 01 Aug 2020
Reachable Sets of Classifiers and Regression Models: (Non-)Robustness Analysis and Robust TrainingMachine-mediated learning (ML), 2020 Anna-Kathrin Kopetzki Stephan Günnemann 164 4 0 28 Jul 2020
Hierarchical Verification for Adversarial RobustnessInternational Conference on Machine Learning (ICML), 2020 Cong Han Lim R. Urtasun Ersin Yumer AAML 132 6 0 23 Jul 2020
Robust Machine Learning via Privacy/Rate-Distortion Theory Ye Wang Shuchin Aeron Adnan Siraj Rakin T. Koike-Akino P. Moulin OOD 152 7 0 22 Jul 2020
SOCRATES: Towards a Unified Platform for Neural Network Analysis Long H. Pham Jiaying Li Jun Sun 116 9 0 22 Jul 2020
Scaling Polyhedral Neural Network Verification on GPUs Christoph Müller F. Serre Gagandeep Singh Markus Püschel Martin Vechev AAML 237 64 0 20 Jul 2020
DiffRNN: Differential Verification of Recurrent Neural Networks Sara Mohammadinejad Brandon Paulsen Chao Wang Jyotirmoy V. Deshmukh 206 13 0 20 Jul 2020
Understanding and Diagnosing Vulnerability under Adversarial Attacks Haizhong Zheng Ziqi Zhang Honglak Lee A. Prakash FAtt AAML 152 6 0 17 Jul 2020
Do Adversarially Robust ImageNet Models Transfer Better?Neural Information Processing Systems (NeurIPS), 2020 Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor Aleksander Madry 306 461 0 16 Jul 2020
Certifiably Adversarially Robust Detection of Out-of-Distribution Data Julian Bitterwolf Alexander Meinke Matthias Hein 328 9 0 16 Jul 2020
Learning perturbation sets for robust machine learningInternational Conference on Learning Representations (ICLR), 2020 Eric Wong J. Zico Kolter OOD 227 84 0 16 Jul 2020
Accelerating Robustness Verification of Deep Neural Networks Guided by Target Labels Wenjie Wan Zhaodi Zhang Yiwei Zhu Min Zhang Fu Song AAML 128 9 0 16 Jul 2020
Adversarial robustness via robust low rank representationsNeural Information Processing Systems (NeurIPS), 2020 Pranjal Awasthi Himanshu Jain A. S. Rawat Aravindan Vijayaraghavan AAML 163 25 0 13 Jul 2020
Security and Machine Learning in the Real World Ivan Evtimov Weidong Cui Ece Kamar Emre Kıcıman Tadayoshi Kohno Haibin Zhang AAML 99 16 0 13 Jul 2020
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test ExamplesNeural Information Processing Systems (NeurIPS), 2020 S. Goldwasser Adam Tauman Kalai Y. Kalai Omar Montasser AAML 178 44 0 10 Jul 2020
Making Adversarial Examples More Transferable and IndistinguishableAAAI Conference on Artificial Intelligence (AAAI), 2020 Junhua Zou Yexin Duan Xin Liu Junyang Qiu Yu Pan Zhisong Pan AAML 168 38 0 08 Jul 2020
Regional Image Perturbation Reduces $L_p$ Norms of Adversarial Examples While Maintaining Model-to-model Transferability Utku Ozbulak Jonathan Peck W. D. Neve Bart Goossens Yvan Saeys Arnout Van Messem AAML 124 2 0 07 Jul 2020
Understanding and Improving Fast Adversarial Training Maksym Andriushchenko Nicolas Flammarion AAML 255 325 0 06 Jul 2020
Trace-Norm Adversarial Examples Ehsan Kazemi Thomas Kerdreux Liqiang Wang 124 2 0 02 Jul 2020
Opportunities and Challenges in Deep Learning Adversarial Robustness: A Survey S. Silva Peyman Najafirad AAML OOD 286 148 0 01 Jul 2020
Determining Sequence of Image Processing Technique (IPT) to Detect Adversarial Attacks Kishor Datta Gupta Zahid Akhtar D. Dasgupta AAML 205 10 0 01 Jul 2020
Neural Network Virtual Sensors for Fuel Injection Quantities with Provable Performance Specifications Eric Wong Tim Schneider Joerg Schmitt Frank R. Schmidt J. Zico Kolter AAML 171 11 0 30 Jun 2020
Black-box Certification and Learning under Adversarial Perturbations H. Ashtiani Vinayak Pathak Ruth Urner AAML 163 20 0 30 Jun 2020