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Adversarial Machine Learning at Scale

4 November 2016

Papers citing "Adversarial Machine Learning at Scale"

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Title
UnMask: Adversarial Detection and Defense Through Robust Feature Alignment Scott Freitas Shang-Tse Chen Zijie J. Wang Duen Horng Chau AAML 61 23 0 21 Feb 2020
Automatic Shortcut Removal for Self-Supervised Representation Learning Matthias Minderer Olivier Bachem N. Houlsby Michael Tschannen SSL 94 73 0 20 Feb 2020
Towards Certifiable Adversarial Sample Detection Ilia Shumailov Yiren Zhao Robert D. Mullins Ross J. Anderson AAML 51 13 0 20 Feb 2020
Boosting Adversarial Training with Hypersphere Embedding Tianyu Pang Xiao Yang Yinpeng Dong Kun Xu Jun Zhu Hang Su AAML 98 156 0 20 Feb 2020
On Adaptive Attacks to Adversarial Example Defenses Florian Tramèr Nicholas Carlini Wieland Brendel Aleksander Madry AAML 297 840 0 19 Feb 2020
Variational Encoder-based Reliable Classification Chitresh Bhushan Zhaoyuan Yang Nurali Virani N. Iyer DRL 41 5 0 19 Feb 2020
Randomized Smoothing of All Shapes and Sizes Greg Yang Tony Duan J. E. Hu Hadi Salman Ilya P. Razenshteyn Jungshian Li AAML 105 216 0 19 Feb 2020
Interpreting Interpretations: Organizing Attribution Methods by Criteria Zifan Wang Piotr (Peter) Mardziel Anupam Datta Matt Fredrikson XAI FAtt 54 17 0 19 Feb 2020
Mind Your Weight(s): A Large-scale Study on Insufficient Machine Learning Model Protection in Mobile Apps Zhichuang Sun Ruimin Sun Long Lu Alan Mislove 90 81 0 18 Feb 2020
Regularized Training and Tight Certification for Randomized Smoothed Classifier with Provable Robustness Huijie Feng Chunpeng Wu Guoyang Chen Weifeng Zhang Y. Ning AAML 71 11 0 17 Feb 2020
CAT: Customized Adversarial Training for Improved Robustness Minhao Cheng Qi Lei Pin-Yu Chen Inderjit Dhillon Cho-Jui Hsieh OOD AAML 102 117 0 17 Feb 2020
Blind Adversarial Network Perturbations Milad Nasr Alireza Bahramali Amir Houmansadr AAML 68 6 0 16 Feb 2020
Adversarial Distributional Training for Robust Deep Learning Yinpeng Dong Zhijie Deng Tianyu Pang Hang Su Jun Zhu OOD 96 123 0 14 Feb 2020
CEB Improves Model Robustness Ian S. Fischer Alexander A. Alemi AAML 137 30 0 13 Feb 2020
The Conditional Entropy Bottleneck Ian S. Fischer OOD 125 122 0 13 Feb 2020
Predictive Power of Nearest Neighbors Algorithm under Random Perturbation Yue Xing Qifan Song Guang Cheng 36 6 0 13 Feb 2020
Over-the-Air Adversarial Flickering Attacks against Video Recognition Networks Roi Pony I. Naeh Shie Mannor AAML 91 54 0 12 Feb 2020
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence S. Raschka Joshua Patterson Corey J. Nolet AI4CE 113 505 0 12 Feb 2020
Improving the affordability of robustness training for DNNs Sidharth Gupta Parijat Dube Ashish Verma AAML 57 15 0 11 Feb 2020
Playing to Learn Better: Repeated Games for Adversarial Learning with Multiple Classifiers P. Dasgupta J. B. Collins Michael McCarrick AAML 44 1 0 10 Feb 2020
Robust binary classification with the 01 loss Yunzhe Xue Meiyan Xie Usman Roshan OOD 24 1 0 09 Feb 2020
Input Validation for Neural Networks via Runtime Local Robustness Verification Jiangchao Liu Liqian Chen A. Miné Ji Wang AAML 52 10 0 09 Feb 2020
Attacking Optical Character Recognition (OCR) Systems with Adversarial Watermarks Lu Chen Wenyuan Xu AAML 44 21 0 08 Feb 2020
Assessing the Adversarial Robustness of Monte Carlo and Distillation Methods for Deep Bayesian Neural Network Classification Meet P. Vadera Satya Narayan Shukla B. Jalaeian Benjamin M. Marlin AAML BDL 45 6 0 07 Feb 2020
An Analysis of Adversarial Attacks and Defenses on Autonomous Driving Models Yao Deng Xi Zheng Tianyi Zhang Chen Chen Guannan Lou Miryung Kim AAML 59 143 0 06 Feb 2020
Minimax Defense against Gradient-based Adversarial Attacks Blerta Lindqvist R. Izmailov AAML 27 0 0 04 Feb 2020
Regularizers for Single-step Adversarial Training S. VivekB. R. Venkatesh Babu AAML 56 7 0 03 Feb 2020
Towards Sharper First-Order Adversary with Quantized Gradients Zhuanghua Liu Ivor W. Tsang AAML 42 0 0 01 Feb 2020
On the Information Bottleneck Problems: Models, Connections, Applications and Information Theoretic Views Milad Sefidgaran Iñaki Estella Aguerri S. Shamai 60 90 0 31 Jan 2020
A4 : Evading Learning-based Adblockers Shitong Zhu Zhongjie Wang Xun Chen Shasha Li Umar Iqbal Zhiyun Qian Kevin S. Chan S. Krishnamurthy Zubair Shafiq AAML 31 3 0 29 Jan 2020
AI-Powered GUI Attack and Its Defensive Methods Ning Yu Zachary Tuttle C. J. Thurnau Emmanuel Mireku AAML 29 6 0 26 Jan 2020
When Wireless Security Meets Machine Learning: Motivation, Challenges, and Research Directions Y. Sagduyu Yi Shi T. Erpek William C. Headley Bryse Flowers G. Stantchev Zhuo Lu AAML 79 39 0 24 Jan 2020
TEAM: An Taylor Expansion-Based Method for Generating Adversarial Examples Yaguan Qian Xi-Ming Zhang Wassim Swaileh Li Wei Bin Wang Jian-Hai Chen Wujie Zhou Jing-Sheng Lei AAML 36 0 0 23 Jan 2020
Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning R. Schuster Tal Schuster Yoav Meri Vitaly Shmatikov AAML 73 39 0 14 Jan 2020
Smooth markets: A basic mechanism for organizing gradient-based learners David Balduzzi Wojciech M. Czarnecki Thomas W. Anthony I. Gemp Edward Hughes Joel Z Leibo Georgios Piliouras T. Graepel 77 15 0 14 Jan 2020
Distortion Agnostic Deep Watermarking Xiyang Luo Ruohan Zhan Huiwen Chang Feng Yang P. Milanfar WIGM 76 165 0 14 Jan 2020
Deep Representation Learning in Speech Processing: Challenges, Recent Advances, and Future Trends S. Latif R. Rana Sara Khalifa Raja Jurdak Junaid Qadir Björn W. Schuller AI4TS 96 82 0 02 Jan 2020
ATHENA: A Framework based on Diverse Weak Defenses for Building Adversarial Defense Meng Jianhai Su Jason M. O'Kane Pooyan Jamshidi AAML 57 7 0 02 Jan 2020
Quantum Adversarial Machine Learning Sirui Lu L. Duan D. Deng AAML 115 102 0 31 Dec 2019
Efficient Adversarial Training with Transferable Adversarial Examples Haizhong Zheng Ziqi Zhang Juncheng Gu Honglak Lee A. Prakash AAML 87 109 0 27 Dec 2019
Grand Challenges in Resilience: Autonomous System Resilience through Design and Runtime Measures S. Bagchi Vaneet Aggarwal Somali Chaterji F. Douglis Aly El Gamal ... K. Marais Prateek Mittal Shaoshuai Mou Xiaokang Qiu G. Scutari AI4CE 150 1 0 25 Dec 2019
Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing Jinyuan Jia Xiaoyu Cao Binghui Wang Neil Zhenqiang Gong AAML 60 96 0 20 Dec 2019
Mitigating large adversarial perturbations on X-MAS (X minus Moving Averaged Samples) Woohyung Chun Sung-Min Hong Junho Huh Inyup Kang AAML 26 0 0 19 Dec 2019
Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable Bytes Keane Lucas Mahmood Sharif Lujo Bauer Michael K. Reiter S. Shintre AAML 96 68 0 19 Dec 2019
$n$ -ML: Mitigating Adversarial Examples via Ensembles of Topologically Manipulated Classifiers Mahmood Sharif Lujo Bauer Michael K. Reiter AAML 48 6 0 19 Dec 2019
Constructing a provably adversarially-robust classifier from a high accuracy one Grzegorz Gluch R. Urbanke AAML 49 2 0 16 Dec 2019
On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration Kanil Patel William H. Beluch Dan Zhang Michael Pfeiffer Bin Yang UQCV 125 30 0 16 Dec 2019
Potential adversarial samples for white-box attacks Amir Nazemi Paul Fieguth AAML 42 18 0 13 Dec 2019
Towards a Robust Classifier: An MDL-Based Method for Generating Adversarial Examples B. Asadi Vijay Varadharajan AAML 43 3 0 11 Dec 2019
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 304 6,354 0 10 Dec 2019