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The Space of Transferable Adversarial Examples

11 April 2017

Dan Boneh

Papers citing "The Space of Transferable Adversarial Examples"

50 / 302 papers shown

Title
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Yue Liu AAML 123 131 0 09 Sep 2020
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective G. R. Machado Eugênio Silva R. Goldschmidt AAML 134 162 0 08 Sep 2020
Simulating Unknown Target Models for Query-Efficient Black-box Attacks Chen Ma Lixing Chen Junhai Yong MLAU OOD 93 17 0 02 Sep 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 113 73 0 07 Aug 2020
TREND: Transferability based Robust ENsemble Design Deepak Ravikumar Sangamesh Kodge Isha Garg Kaushik Roy OOD AAML 30 4 0 04 Aug 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 76 129 0 13 Jul 2020
Knowledge Distillation Beyond Model Compression F. Sarfraz Elahe Arani Bahram Zonooz 76 42 0 03 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
Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability Kaizhao Liang Jacky Y. Zhang Wei Ping Zhuolin Yang Oluwasanmi Koyejo Yangqiu Song AAML 129 26 0 25 Jun 2020
Adversarial Attacks for Multi-view Deep Models Xuli Sun Shiliang Sun AAML 29 0 0 19 Jun 2020
The Pitfalls of Simplicity Bias in Neural Networks Harshay Shah Kaustav Tamuly Aditi Raghunathan Prateek Jain Praneeth Netrapalli AAML 76 364 0 13 Jun 2020
Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors Gerda Bortsova C. González-Gonzalo S. Wetstein Florian Dubost Ioannis Katramados ... Bram van Ginneken J. Pluim M. Veta Clara I. Sánchez Marleen de Bruijne AAML MedIm 38 131 0 11 Jun 2020
On the Effectiveness of Regularization Against Membership Inference Attacks Yigitcan Kaya Sanghyun Hong Tudor Dumitras 87 28 0 09 Jun 2020
Tricking Adversarial Attacks To Fail Blerta Lindqvist AAML 48 0 0 08 Jun 2020
Enhancing Resilience of Deep Learning Networks by Means of Transferable Adversaries M. Seiler Heike Trautmann P. Kerschke AAML 24 0 0 27 May 2020
Universalization of any adversarial attack using very few test examples Sandesh Kamath Amit Deshpande K. Subrahmanyam Vineeth N. Balasubramanian FedML AAML 36 1 0 18 May 2020
Increased-confidence adversarial examples for deep learning counter-forensics Wenjie Li B. Tondi R. Ni Mauro Barni AAML 24 2 0 12 May 2020
Blind Backdoors in Deep Learning Models Eugene Bagdasaryan Vitaly Shmatikov AAML FedML SILM 152 309 0 08 May 2020
MAZE: Data-Free Model Stealing Attack Using Zeroth-Order Gradient Estimation Sanjay Kariyappa A. Prakash Moinuddin K. Qureshi AAML 73 153 0 06 May 2020
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability Nathan Inkawhich Kevin J. Liang Binghui Wang Matthew J. Inkawhich Lawrence Carin Yiran Chen AAML 87 90 0 29 Apr 2020
Transferable Perturbations of Deep Feature Distributions Nathan Inkawhich Kevin J. Liang Lawrence Carin Yiran Chen AAML 73 87 0 27 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
SOAR: Second-Order Adversarial Regularization A. Ma Fartash Faghri Nicolas Papernot Amir-massoud Farahmand AAML 35 4 0 04 Apr 2020
Do Deep Minds Think Alike? Selective Adversarial Attacks for Fine-Grained Manipulation of Multiple Deep Neural Networks Zain Khan Jirong Yi R. Mudumbai Xiaodong Wu Weiyu Xu AAML MLAU 51 1 0 26 Mar 2020
PoisHygiene: Detecting and Mitigating Poisoning Attacks in Neural Networks Junfeng Guo Zelun Kong Cong Liu AAML 47 1 0 24 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
Adversarial Perturbations Fool Deepfake Detectors Apurva Gandhi Shomik Jain AAML 66 106 0 24 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
Face-Off: Adversarial Face Obfuscation Varun Chandrasekaran Chuhan Gao Brian Tang Kassem Fawaz S. Jha Suman Banerjee PICV 81 44 0 19 Mar 2020
GeoDA: a geometric framework for black-box adversarial attacks A. Rahmati Seyed-Mohsen Moosavi-Dezfooli P. Frossard H. Dai MLAU AAML 143 120 0 13 Mar 2020
Denoised Smoothing: A Provable Defense for Pretrained Classifiers Hadi Salman Mingjie Sun Greg Yang Ashish Kapoor J. Zico Kolter 94 23 0 04 Mar 2020
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness Ahmadreza Jeddi M. Shafiee Michelle Karg C. Scharfenberger A. Wong OOD AAML 126 67 0 02 Mar 2020
Randomization matters. How to defend against strong adversarial attacks Rafael Pinot Raphael Ettedgui Geovani Rizk Y. Chevaleyre Jamal Atif AAML 114 60 0 26 Feb 2020
On the Matrix-Free Generation of Adversarial Perturbations for Black-Box Attacks Hisaichi Shibata S. Hanaoka Y. Nomura Naoto Hayashi O. Abe AAML 17 0 0 18 Feb 2020
Analysis of Random Perturbations for Robust Convolutional Neural Networks Adam Dziedzic S. Krishnan OOD AAML 59 1 0 08 Feb 2020
Minimax Defense against Gradient-based Adversarial Attacks Blerta Lindqvist R. Izmailov AAML 22 0 0 04 Feb 2020
Tiny noise, big mistakes: Adversarial perturbations induce errors in Brain-Computer Interface spellers Xiao Zhang Dongrui Wu L. Ding Hanbin Luo Chin-Teng Lin T. Jung Ricardo Chavarriaga AAML 91 60 0 30 Jan 2020
Challenges and Countermeasures for Adversarial Attacks on Deep Reinforcement Learning Inaam Ilahi Muhammad Usama Junaid Qadir M. Janjua Ala I. Al-Fuqaha D. Hoang Dusit Niyato AAML 143 136 0 27 Jan 2020
Ensemble Noise Simulation to Handle Uncertainty about Gradient-based Adversarial Attacks Rehana Mahfuz R. Sahay Aly El Gamal AAML 29 2 0 26 Jan 2020
Quantum Adversarial Machine Learning Sirui Lu L. Duan D. Deng AAML 108 102 0 31 Dec 2019
A Survey of Game Theoretic Approaches for Adversarial Machine Learning in Cybersecurity Tasks P. Dasgupta J. B. Collins AAML 38 43 0 04 Dec 2019
Walking on the Edge: Fast, Low-Distortion Adversarial Examples Hanwei Zhang Yannis Avrithis Teddy Furon Laurent Amsaleg AAML 50 46 0 04 Dec 2019
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples Nils Lukas Yuxuan Zhang Florian Kerschbaum MLAU FedML AAML 112 146 0 02 Dec 2019
Towards Security Threats of Deep Learning Systems: A Survey Yingzhe He Guozhu Meng Kai Chen Xingbo Hu Jinwen He AAML ELM 56 14 0 28 Nov 2019
Shared Visual Abstractions Tom White 38 5 0 19 Nov 2019
SMART: Skeletal Motion Action Recognition aTtack He Wang Feixiang He Zexi Peng Yong-Liang Yang Tianjia Shao Kun Zhou David C. Hogg AAML 52 5 0 16 Nov 2019
Defending Against Model Stealing Attacks with Adaptive Misinformation Sanjay Kariyappa Moinuddin K. Qureshi MLAU AAML 64 109 0 16 Nov 2019
Learning To Characterize Adversarial Subspaces Xiaofeng Mao YueFeng Chen Yuhong Li Yuan He Hui Xue AAML 68 11 0 15 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 124 105 0 13 Nov 2019
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey Olakunle Ibitoye Rana Abou-Khamis Mohamed el Shehaby Ashraf Matrawy M. O. Shafiq AAML 95 70 0 06 Nov 2019