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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"

50 / 1,929 papers shown

Title
Addressing Neural Network Robustness with Mixup and Targeted Labeling Adversarial Training Alfred Laugros A. Caplier Matthieu Ospici AAML 119 19 0 19 Aug 2020
CCA: Exploring the Possibility of Contextual Camouflage Attack on Object Detection Shengnan Hu Yang Zhang Sumit Laha A. Sharma H. Foroosh AAML 40 8 0 19 Aug 2020
Adversarial Attack and Defense Strategies for Deep Speaker Recognition Systems Arindam Jati Chin-Cheng Hsu Monisankha Pal Raghuveer Peri Wael AbdAlmageed Shrikanth Narayanan AAML 79 67 0 18 Aug 2020
Adversarial Concurrent Training: Optimizing Robustness and Accuracy Trade-off of Deep Neural Networks Elahe Arani F. Sarfraz Bahram Zonooz AAML 60 9 0 16 Aug 2020
Learning to Learn from Mistakes: Robust Optimization for Adversarial Noise A. Serban E. Poll Joost Visser AAML 78 1 0 12 Aug 2020
Adversarial Training with Fast Gradient Projection Method against Synonym Substitution based Text Attacks Xiaosen Wang Yichen Yang Yihe Deng Kun He OOD AAML 51 3 0 09 Aug 2020
Investigating maximum likelihood based training of infinite mixtures for uncertainty quantification Sina Daubener Asja Fischer BDL UQCV 63 2 0 07 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 118 73 0 07 Aug 2020
Stronger and Faster Wasserstein Adversarial Attacks Kaiwen Wu Allen Wang Yaoliang Yu AAML 85 32 0 06 Aug 2020
TREND: Transferability based Robust ENsemble Design Deepak Ravikumar Sangamesh Kodge Isha Garg Kaushik Roy OOD AAML 49 4 0 04 Aug 2020
Anti-Bandit Neural Architecture Search for Model Defense Hanlin Chen Baochang Zhang Shenjun Xue Xuan Gong Hong Liu Rongrong Ji David Doermann AAML 58 35 0 03 Aug 2020
Trojaning Language Models for Fun and Profit Xinyang Zhang Zheng Zhang Shouling Ji Ting Wang SILM AAML 98 140 0 01 Aug 2020
Towards Class-Oriented Poisoning Attacks Against Neural Networks Bingyin Zhao Yingjie Lao SILM AAML 24 18 0 31 Jul 2020
A Data Augmentation-based Defense Method Against Adversarial Attacks in Neural Networks Yi Zeng Han Qiu G. Memmi Meikang Qiu AAML 66 51 0 30 Jul 2020
A General Framework For Detecting Anomalous Inputs to DNN Classifiers Jayaram Raghuram Varun Chandrasekaran S. Jha Suman Banerjee AAML 106 35 0 29 Jul 2020
Stylized Adversarial Defense Muzammal Naseer Salman Khan Munawar Hayat Fahad Shahbaz Khan Fatih Porikli GAN AAML 80 16 0 29 Jul 2020
Attacking and Defending Machine Learning Applications of Public Cloud Dou Goodman Xin Hao SILM AAML 66 7 0 27 Jul 2020
RANDOM MASK: Towards Robust Convolutional Neural Networks Tiange Luo Tianle Cai Mengxiao Zhang Siyu Chen Liwei Wang AAML OOD 92 17 0 27 Jul 2020
Robust Machine Learning via Privacy/Rate-Distortion Theory Ye Wang Shuchin Aeron Adnan Siraj Rakin T. Koike-Akino P. Moulin OOD 74 6 0 22 Jul 2020
Robust Image Classification Using A Low-Pass Activation Function and DCT Augmentation Md Tahmid Hossain S. Teng Ferdous Sohel Guojun Lu 106 10 0 18 Jul 2020
Neural Networks with Recurrent Generative Feedback Yujia Huang James Gornet Sihui Dai Zhiding Yu T. Nguyen Doris Y. Tsao Anima Anandkumar AAML GAN 82 41 0 17 Jul 2020
Certifiably Adversarially Robust Detection of Out-of-Distribution Data Julian Bitterwolf Alexander Meinke Matthias Hein 65 9 0 16 Jul 2020
Adversarial Examples and Metrics Nico Döttling Kathrin Grosse Michael Backes Ian Molloy AAML 49 0 0 14 Jul 2020
Towards robust sensing for Autonomous Vehicles: An adversarial perspective Apostolos Modas Ricardo Sánchez-Matilla P. Frossard Andrea Cavallaro AAML 63 35 0 14 Jul 2020
SoK: The Faults in our ASRs: An Overview of Attacks against Automatic Speech Recognition and Speaker Identification Systems H. Abdullah Kevin Warren Vincent Bindschaedler Nicolas Papernot Patrick Traynor AAML 78 129 0 13 Jul 2020
Security and Machine Learning in the Real World Ivan Evtimov Weidong Cui Ece Kamar Emre Kıcıman Tadayoshi Kohno Jingkai Li AAML 57 15 0 13 Jul 2020
Understanding Adversarial Examples from the Mutual Influence of Images and Perturbations Chaoning Zhang Philipp Benz Tooba Imtiaz In-So Kweon SSL AAML 87 119 0 13 Jul 2020
Generating Adversarial Inputs Using A Black-box Differential Technique J. Matos Lucas C. Cordeiro Marcelo d’Amorim Xiaowei Huang AAML 29 0 0 10 Jul 2020
Improving Adversarial Robustness by Enforcing Local and Global Compactness Anh-Vu Bui Trung Le He Zhao Paul Montague O. deVel Tamas Abraham Dinh Q. Phung AAML 62 24 0 10 Jul 2020
Boundary thickness and robustness in learning models Yaoqing Yang Rekha Khanna Yaodong Yu A. Gholami Kurt Keutzer Joseph E. Gonzalez Kannan Ramchandran Michael W. Mahoney OOD 72 42 0 09 Jul 2020
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning Hongyi Wang Kartik K. Sreenivasan Shashank Rajput Harit Vishwakarma Saurabh Agarwal Jy-yong Sohn Kangwook Lee Dimitris Papailiopoulos FedML 118 616 0 09 Jul 2020
Green Lighting ML: Confidentiality, Integrity, and Availability of Machine Learning Systems in Deployment Abhishek Gupta Erick Galinkin 32 3 0 09 Jul 2020
How benign is benign overfitting? Amartya Sanyal P. Dokania Varun Kanade Philip Torr NoLa AAML 89 58 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 34 2 0 07 Jul 2020
Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain Ishai Rosenberg A. Shabtai Yuval Elovici Lior Rokach AAML 89 12 0 05 Jul 2020
On Connections between Regularizations for Improving DNN Robustness Yiwen Guo Long Chen Yurong Chen Changshui Zhang AAML 54 14 0 04 Jul 2020
Trace-Norm Adversarial Examples Ehsan Kazemi Thomas Kerdreux Liqiang Wang 66 2 0 02 Jul 2020
Generating Adversarial Examples with Controllable Non-transferability Renzhi Wang Tianwei Zhang Xiaofei Xie Lei Ma Cong Tian Felix Juefei Xu Yang Liu SILM AAML 80 3 0 02 Jul 2020
Determining Sequence of Image Processing Technique (IPT) to Detect Adversarial Attacks Kishor Datta Gupta Zahid Akhtar D. Dasgupta AAML 65 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 72 8 0 30 Jun 2020
Towards Robust LiDAR-based Perception in Autonomous Driving: General Black-box Adversarial Sensor Attack and Countermeasures Jiachen Sun Yulong Cao Qi Alfred Chen Z. Morley Mao AAML 74 244 0 30 Jun 2020
Adversarial Deep Ensemble: Evasion Attacks and Defenses for Malware Detection Deqiang Li Qianmu Li AAML 77 126 0 30 Jun 2020
Biologically Inspired Mechanisms for Adversarial Robustness M. V. Reddy Andrzej Banburski Nishka Pant T. Poggio AAML 70 46 0 29 Jun 2020
Improving Calibration through the Relationship with Adversarial Robustness Yao Qin Xuezhi Wang Alex Beutel Ed H. Chi AAML 86 25 0 29 Jun 2020
Geometry-Inspired Top-k Adversarial Perturbations Nurislam Tursynbek Aleksandr Petiushko Ivan Oseledets AAML 83 10 0 28 Jun 2020
ATOM: Robustifying Out-of-distribution Detection Using Outlier Mining Jiefeng Chen Yixuan Li Xi Wu Yingyu Liang S. Jha OODD 102 140 0 26 Jun 2020
Diverse Knowledge Distillation (DKD): A Solution for Improving The Robustness of Ensemble Models Against Adversarial Attacks Ali Mirzaeian Jana Kosecka Houman Homayoun Tinoosh Mohsening Avesta Sasan FedML AAML 55 3 0 26 Jun 2020
Proper Network Interpretability Helps Adversarial Robustness in Classification Akhilan Boopathy Sijia Liu Gaoyuan Zhang Cynthia Liu Pin-Yu Chen Shiyu Chang Luca Daniel AAML FAtt 132 66 0 26 Jun 2020
Smooth Adversarial Training Cihang Xie Mingxing Tan Boqing Gong Alan Yuille Quoc V. Le OOD 94 154 0 25 Jun 2020
Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability Kaizhao Liang Jacky Y. Zhang Wei Ping Zhuolin Yang Oluwasanmi Koyejo Yangqiu Song AAML 140 26 0 25 Jun 2020