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Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

1 February 2018

Papers citing "Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples"

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DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses Yaxin Li Wei Jin Han Xu Jiliang Tang AAML 90 133 0 13 May 2020
Provable Robust Classification via Learned Smoothed Densities Saeed Saremi R. Srivastava AAML 88 3 0 09 May 2020
Efficient Exact Verification of Binarized Neural Networks Kai Jia Martin Rinard AAML MQ 48 59 0 07 May 2020
GraCIAS: Grassmannian of Corrupted Images for Adversarial Security Ankita Shukla Pavan Turaga Saket Anand AAML 39 1 0 06 May 2020
Enhancing Intrinsic Adversarial Robustness via Feature Pyramid Decoder Guanlin Li Shuya Ding Jun Luo Chang-rui Liu AAML 107 19 0 06 May 2020
Adversarial Training against Location-Optimized Adversarial Patches Sukrut Rao David Stutz Bernt Schiele AAML 84 93 0 05 May 2020
Robust Encodings: A Framework for Combating Adversarial Typos Erik Jones Robin Jia Aditi Raghunathan Percy Liang AAML 321 103 0 04 May 2020
A Causal View on Robustness of Neural Networks Cheng Zhang Kun Zhang Yingzhen Li CML OOD 109 85 0 03 May 2020
Bullseye Polytope: A Scalable Clean-Label Poisoning Attack with Improved Transferability H. Aghakhani Dongyu Meng Yu-Xiang Wang Christopher Kruegel Giovanni Vigna AAML 77 104 0 01 May 2020
Does Data Augmentation Improve Generalization in NLP? Rohan Jha Charles Lovering Ellie Pavlick 80 10 0 30 Apr 2020
Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks Pranjal Awasthi Natalie Frank M. Mohri AAML 95 58 0 28 Apr 2020
Harnessing adversarial examples with a surprisingly simple defense Ali Borji AAML 31 0 0 26 Apr 2020
Improved Adversarial Training via Learned Optimizer Yuanhao Xiong Cho-Jui Hsieh AAML 81 31 0 25 Apr 2020
RAIN: A Simple Approach for Robust and Accurate Image Classification Networks Jiawei Du Hanshu Yan Vincent Y. F. Tan Qiufeng Wang Rick Siow Mong Goh Jiashi Feng AAML 16 0 0 24 Apr 2020
Adversarial Attacks and Defenses: An Interpretation Perspective Ninghao Liu Mengnan Du Ruocheng Guo Huan Liu Helen Zhou AAML 61 8 0 23 Apr 2020
Ensemble Generative Cleaning with Feedback Loops for Defending Adversarial Attacks Jianhe Yuan Zhihai He AAML 64 22 0 23 Apr 2020
Improved Noise and Attack Robustness for Semantic Segmentation by Using Multi-Task Training with Self-Supervised Depth Estimation Marvin Klingner Andreas Bär Tim Fingscheidt AAML 95 41 0 23 Apr 2020
Neural Network Laundering: Removing Black-Box Backdoor Watermarks from Deep Neural Networks William Aiken Hyoungshick Kim Simon S. Woo 40 64 0 22 Apr 2020
Discovering Imperfectly Observable Adversarial Actions using Anomaly Detection Olga Petrova K. Durkota Galina Alperovich Karel Horak Michal Najman B. Bosanský Viliam Lisý AAML 16 1 0 22 Apr 2020
Provably robust deep generative models Filipe Condessa Zico Kolter AAML OOD 38 5 0 22 Apr 2020
Scalable Attack on Graph Data by Injecting Vicious Nodes Jihong Wang Minnan Luo Fnu Suya Jundong Li Z. Yang Q. Zheng AAML GNN 87 90 0 22 Apr 2020
Testing Machine Translation via Referential Transparency Pinjia He Clara Meister Z. Su 59 51 0 22 Apr 2020
Single-step Adversarial training with Dropout Scheduling S. VivekB. R. Venkatesh Babu OOD AAML 65 73 0 18 Apr 2020
A Framework for Enhancing Deep Neural Networks Against Adversarial Malware Deqiang Li Qianmu Li Yanfang Ye Shouhuai Xu AAML 75 13 0 15 Apr 2020
Adversarial Weight Perturbation Helps Robust Generalization Dongxian Wu Shutao Xia Yisen Wang OOD AAML 60 17 0 13 Apr 2020
Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement Learning Michael Everett Bjorn Lutjens Jonathan P. How AAML 53 42 0 11 Apr 2020
Adversarial Attacks on Machine Learning Cybersecurity Defences in Industrial Control Systems Eirini Anthi Lowri Williams Matilda Rhode Pete Burnap Adam Wedgbury AAML 51 126 0 10 Apr 2020
On Adversarial Examples and Stealth Attacks in Artificial Intelligence Systems I. Tyukin D. Higham A. Gorban AAML 46 39 0 09 Apr 2020
Approximate Manifold Defense Against Multiple Adversarial Perturbations Jay Nandy Wynne Hsu Mong Li Lee AAML 65 12 0 05 Apr 2020
SOAR: Second-Order Adversarial Regularization A. Ma Fartash Faghri Nicolas Papernot Amir-massoud Farahmand AAML 35 4 0 04 Apr 2020
Evading Deepfake-Image Detectors with White- and Black-Box Attacks Nicholas Carlini Hany Farid AAML 81 150 0 01 Apr 2020
Towards Achieving Adversarial Robustness by Enforcing Feature Consistency Across Bit Planes Sravanti Addepalli S. VivekB. Arya Baburaj Gaurang Sriramanan R. Venkatesh Babu AAML 31 32 0 01 Apr 2020
MetaPoison: Practical General-purpose Clean-label Data Poisoning Wenjie Huang Jonas Geiping Liam H. Fowl Gavin Taylor Tom Goldstein 132 190 0 01 Apr 2020
Inverting Gradients -- How easy is it to break privacy in federated learning? Jonas Geiping Hartmut Bauermeister Hannah Dröge Michael Moeller FedML 136 1,238 0 31 Mar 2020
Improved Gradient based Adversarial Attacks for Quantized Networks Kartik Gupta Thalaiyasingam Ajanthan MQ 58 19 0 30 Mar 2020
Towards Deep Learning Models Resistant to Large Perturbations Amirreza Shaeiri Rozhin Nobahari M. Rohban OOD AAML 81 12 0 30 Mar 2020
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning Tianlong Chen Sijia Liu Shiyu Chang Yu Cheng Lisa Amini Zhangyang Wang AAML 71 250 0 28 Mar 2020
Adversarial Imitation Attack Mingyi Zhou Jing Wu Yipeng Liu Xiaolin Huang Shuaicheng Liu Xiang Zhang Ce Zhu AAML 39 0 0 28 Mar 2020
DaST: Data-free Substitute Training for Adversarial Attacks Mingyi Zhou Jing Wu Yipeng Liu Shuaicheng Liu Ce Zhu 86 145 0 28 Mar 2020
A Separation Result Between Data-oblivious and Data-aware Poisoning Attacks Samuel Deng Sanjam Garg S. Jha Saeed Mahloujifar Mohammad Mahmoody Abhradeep Thakurta 37 3 0 26 Mar 2020
Defense Through Diverse Directions Christopher M. Bender Yang Li Yifeng Shi Michael K. Reiter Junier B. Oliva AAML 51 4 0 24 Mar 2020
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 396 378 0 24 Mar 2020
Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-Linear Activations Saima Sharmin Nitin Rathi Priyadarshini Panda Kaushik Roy AAML 159 92 0 23 Mar 2020
Adversarial Attacks on Monocular Depth Estimation Ziqi Zhang Xinge Zhu Yingwei Li Xiangqun Chen Yao Guo AAML MDE 83 26 0 23 Mar 2020
Robust Out-of-distribution Detection for Neural Networks Jiefeng Chen Yixuan Li Xi Wu Yingyu Liang S. Jha OODD 231 88 0 21 Mar 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability Maximilian Augustin Alexander Meinke Matthias Hein OOD 193 102 0 20 Mar 2020
Investigating Image Applications Based on Spatial-Frequency Transform and Deep Learning Techniques Qinkai Zheng Han Qiu G. Memmi Isabelle Bloch 27 0 0 20 Mar 2020
Breaking certified defenses: Semantic adversarial examples with spoofed robustness certificates Amin Ghiasi Ali Shafahi Tom Goldstein 102 55 0 19 Mar 2020
RAB: Provable Robustness Against Backdoor Attacks Maurice Weber Xiaojun Xu Bojan Karlas Ce Zhang Yue Liu AAML 120 164 0 19 Mar 2020
SAT: Improving Adversarial Training via Curriculum-Based Loss Smoothing Chawin Sitawarin S. Chakraborty David Wagner AAML 74 40 0 18 Mar 2020