Exploring the Space of Black-box Attacks on Deep Neural Networks

Exploring the Space of Black-box Attacks on Deep Neural Networks

27 December 2017

Papers citing "Exploring the Space of Black-box Attacks on Deep Neural Networks"

19 / 19 papers shown

Title
Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker Sihui Dai Wen-Luan Ding A. Bhagoji Daniel Cullina Ben Y. Zhao Haitao Zheng Prateek Mittal AAML 37 2 0 21 Feb 2023
DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification A. Ćiprijanović Diana Kafkes Gregory F. Snyder F. Sánchez G. Perdue K. Pedro Brian D. Nord Sandeep Madireddy Stefan M. Wild AAML 42 15 0 28 Dec 2021
Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks Huichen Li Linyi Li Xiaojun Xu Xiaolu Zhang Shuang Yang Bo-wen Li AAML 33 17 0 25 Feb 2021
Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPS Felix O. Olowononi D. Rawat Chunmei Liu 38 134 0 14 Feb 2021
A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning Hongjun Wang Guanbin Li Xiaobai Liu Liang Lin GAN AAML 21 22 0 15 Oct 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 32 73 0 07 Aug 2020
Adversarial Training against Location-Optimized Adversarial Patches Sukrut Rao David Stutz Bernt Schiele AAML 19 92 0 05 May 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 72 63 0 02 Mar 2020
On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method Pu Zhao Sijia Liu Pin-Yu Chen Nghia Hoang Kaidi Xu B. Kailkhura Xue Lin AAML 32 54 0 26 Jul 2019
Characterizing Attacks on Deep Reinforcement Learning Xinlei Pan Chaowei Xiao Warren He Shuang Yang Jian Peng ... Jinfeng Yi Zijiang Yang Mingyan D. Liu Bo-wen Li D. Song AAML 14 69 0 21 Jul 2019
Defending Against Adversarial Attacks Using Random Forests Yifan Ding Liqiang Wang Huan Zhang Jinfeng Yi Deliang Fan Boqing Gong AAML 21 14 0 16 Jun 2019
Taking Care of The Discretization Problem: A Comprehensive Study of the Discretization Problem and A Black-Box Adversarial Attack in Discrete Integer Domain Lei Bu Yuchao Duan Fu Song Zhe Zhao AAML 37 18 0 19 May 2019
Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation Chaowei Xiao Ruizhi Deng Bo-wen Li Feng Yu M. Liu D. Song AAML 19 99 0 11 Oct 2018
Enabling Trust in Deep Learning Models: A Digital Forensics Case Study Aditya K Slawomir Grzonkowski NhienAn Lekhac 19 27 0 03 Aug 2018
Query-Efficient Hard-label Black-box Attack:An Optimization-based Approach Minhao Cheng Thong Le Pin-Yu Chen Jinfeng Yi Huan Zhang Cho-Jui Hsieh AAML 43 346 0 12 Jul 2018
Why do deep convolutional networks generalize so poorly to small image transformations? Aharon Azulay Yair Weiss 37 557 0 30 May 2018
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks Chun-Chen Tu Pai-Shun Ting Pin-Yu Chen Sijia Liu Huan Zhang Jinfeng Yi Cho-Jui Hsieh Shin-Ming Cheng MLAU AAML 26 395 0 30 May 2018
Generative Adversarial Perturbations Omid Poursaeed Isay Katsman Bicheng Gao Serge J. Belongie AAML GAN WIGM 31 351 0 06 Dec 2017
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 326 5,849 0 08 Jul 2016