Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples

24 May 2016

Papers citing "Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples"

50 / 360 papers shown

Title
All You Need is RAW: Defending Against Adversarial Attacks with Camera Image Pipelines Yuxuan Zhang B. Dong Felix Heide AAML 26 8 0 16 Dec 2021
The Fundamental Limits of Interval Arithmetic for Neural Networks M. Mirman Maximilian Baader Martin Vechev 32 6 0 09 Dec 2021
A Unified Framework for Adversarial Attack and Defense in Constrained Feature Space Thibault Simonetto Salijona Dyrmishi Salah Ghamizi Maxime Cordy Yves Le Traon AAML 24 21 0 02 Dec 2021
Adv-4-Adv: Thwarting Changing Adversarial Perturbations via Adversarial Domain Adaptation Tianyue Zheng Zhe Chen Shuya Ding Chao Cai Jun Luo AAML 35 5 0 01 Dec 2021
TnT Attacks! Universal Naturalistic Adversarial Patches Against Deep Neural Network Systems Bao Gia Doan Minhui Xue Shiqing Ma Ehsan Abbasnejad Damith C. Ranasinghe AAML 41 53 0 19 Nov 2021
DeepSteal: Advanced Model Extractions Leveraging Efficient Weight Stealing in Memories Adnan Siraj Rakin Md Hafizul Islam Chowdhuryy Fan Yao Deliang Fan AAML MIACV 42 110 0 08 Nov 2021
Natural Adversarial Objects Felix Lau Nishant Subramani Sasha Harrison Aerin Kim E. Branson Rosanne Liu 26 7 0 07 Nov 2021
Confidential Machine Learning Computation in Untrusted Environments: A Systems Security Perspective Kha Dinh Duy Taehyun Noh Siwon Huh Hojoon Lee 56 9 0 05 Nov 2021
A Layer-wise Adversarial-aware Quantization Optimization for Improving Robustness Chang Song Riya Ranjan H. Li MQ 21 4 0 23 Oct 2021
Black-box Adversarial Attacks on Network-wide Multi-step Traffic State Prediction Models Bibek Poudel Weizi Li AAML MLAU OOD 13 20 0 17 Oct 2021
Parameterizing Activation Functions for Adversarial Robustness Sihui Dai Saeed Mahloujifar Prateek Mittal AAML 47 32 0 11 Oct 2021
Demystifying the Transferability of Adversarial Attacks in Computer Networks Ehsan Nowroozi Yassine Mekdad Mohammad Hajian Berenjestanaki Mauro Conti Abdeslam El Fergougui AAML 42 32 0 09 Oct 2021
Robust Feature-Level Adversaries are Interpretability Tools Stephen Casper Max Nadeau Dylan Hadfield-Menell Gabriel Kreiman AAML 53 27 0 07 Oct 2021
Back in Black: A Comparative Evaluation of Recent State-Of-The-Art Black-Box Attacks Kaleel Mahmood Rigel Mahmood Ethan Rathbun Marten van Dijk AAML 19 22 0 29 Sep 2021
Adversarial Transfer Attacks With Unknown Data and Class Overlap Luke E. Richards A. Nguyen Ryan Capps Steven D. Forsythe Cynthia Matuszek Edward Raff AAML 41 7 0 23 Sep 2021
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest Gilad Cohen Raja Giryes AAML 42 4 0 16 Sep 2021
Evolving Architectures with Gradient Misalignment toward Low Adversarial Transferability K. Operiano W. Pora H. Iba Hiroshi Kera AAML 42 1 0 13 Sep 2021
Training Meta-Surrogate Model for Transferable Adversarial Attack Yunxiao Qin Yuanhao Xiong Jinfeng Yi Cho-Jui Hsieh AAML 20 18 0 05 Sep 2021
Regional Adversarial Training for Better Robust Generalization Chuanbiao Song Yanbo Fan Yichen Yang Baoyuan Wu Yiming Li Zhifeng Li Kun He AAML OOD 21 6 0 02 Sep 2021
Shared Certificates for Neural Network Verification Marc Fischer C. Sprecher Dimitar I. Dimitrov Gagandeep Singh Martin Vechev AAML 28 12 0 01 Sep 2021
Morphence: Moving Target Defense Against Adversarial Examples Abderrahmen Amich Birhanu Eshete AAML 37 24 0 31 Aug 2021
Disrupting Adversarial Transferability in Deep Neural Networks Christopher Wiedeman Ge Wang AAML 36 8 0 27 Aug 2021
Physical Adversarial Attacks on an Aerial Imagery Object Detector Andrew Du Bo Chen Tat-Jun Chin Yee Wei Law Michele Sasdelli Ramesh Rajasegaran Dillon Campbell AAML 33 60 0 26 Aug 2021
Exploring Transferable and Robust Adversarial Perturbation Generation from the Perspective of Network Hierarchy Ruikui Wang Yuanfang Guo Ruijie Yang Yunhong Wang AAML 17 3 0 16 Aug 2021
Optical Adversarial Attack Abhiram Gnanasambandam A. Sherman Stanley H. Chan AAML 35 65 0 13 Aug 2021
On the Certified Robustness for Ensemble Models and Beyond Zhuolin Yang Linyi Li Xiaojun Xu B. Kailkhura Tao Xie Bo-wen Li AAML 29 48 0 22 Jul 2021
Discriminator-Free Generative Adversarial Attack Shaohao Lu Yuqiao Xian Ke Yan Yi Hu Xing Sun Xiaowei Guo Feiyue Huang Weishi Zheng AAML GAN 35 20 0 20 Jul 2021
Model Transferability With Responsive Decision Subjects Yatong Chen Zeyu Tang Kun Zhang Yang Liu 43 10 0 13 Jul 2021
ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients Alessandro Cappelli Julien Launay Laurent Meunier Ruben Ohana Iacopo Poli AAML 29 4 0 06 Jul 2021
GradDiv: Adversarial Robustness of Randomized Neural Networks via Gradient Diversity Regularization Sungyoon Lee Hoki Kim Jaewook Lee AAML 35 52 0 06 Jul 2021
Data Poisoning Won't Save You From Facial Recognition Evani Radiya-Dixit Sanghyun Hong Nicholas Carlini Florian Tramèr AAML PICV 22 57 0 28 Jun 2021
Localized Uncertainty Attacks Ousmane Amadou Dia Theofanis Karaletsos C. Hazirbas Cristian Canton Ferrer I. Kabul E. Meijer AAML 24 2 0 17 Jun 2021
Adversarial Robustness via Fisher-Rao Regularization Marine Picot Francisco Messina Malik Boudiaf Fabrice Labeau Ismail Ben Ayed Pablo Piantanida AAML 31 23 0 12 Jun 2021
A Little Robustness Goes a Long Way: Leveraging Robust Features for Targeted Transfer Attacks Jacob Mitchell Springer Melanie Mitchell Garrett Kenyon AAML 31 43 0 03 Jun 2021
Concurrent Adversarial Learning for Large-Batch Training Yong Liu Xiangning Chen Minhao Cheng Cho-Jui Hsieh Yang You ODL 36 13 0 01 Jun 2021
Transferable Sparse Adversarial Attack Ziwen He Wei Wang Jing Dong Tieniu Tan AAML 19 20 0 31 May 2021
Real-time Detection of Practical Universal Adversarial Perturbations Kenneth T. Co Luis Muñoz-González Leslie Kanthan Emil C. Lupu AAML 33 6 0 16 May 2021
BAARD: Blocking Adversarial Examples by Testing for Applicability, Reliability and Decidability Luke Chang Katharina Dost Kaiqi Zhao Ambra Demontis Fabio Roli Gillian Dobbie Jörg Simon Wicker AAML 27 2 0 02 May 2021
Who's Afraid of Adversarial Transferability? Ziv Katzir Yuval Elovici SILM AAML 27 9 0 02 May 2021
Robustness Tests of NLP Machine Learning Models: Search and Semantically Replace Rahul Singh Karan Jindal Yufei Yu Hanyu Yang Tarun Joshi Matthew A. Campbell Wayne B. Shoumaker 58 2 0 20 Apr 2021
Mitigating Adversarial Attack for Compute-in-Memory Accelerator Utilizing On-chip Finetune Shanshi Huang Hongwu Jiang Shimeng Yu AAML 26 3 0 13 Apr 2021
A Backdoor Attack against 3D Point Cloud Classifiers Zhen Xiang David J. Miller Siheng Chen Xi Li G. Kesidis 3DPC AAML 36 76 0 12 Apr 2021
FACESEC: A Fine-grained Robustness Evaluation Framework for Face Recognition Systems Liang Tong Zhengzhang Chen Jingchao Ni Wei Cheng Dongjin Song Haifeng Chen Yevgeniy Vorobeychik CVBM AAML 32 19 0 08 Apr 2021
On the Robustness of Vision Transformers to Adversarial Examples Kaleel Mahmood Rigel Mahmood Marten van Dijk ViT 33 219 0 31 Mar 2021
SoK: A Modularized Approach to Study the Security of Automatic Speech Recognition Systems Yuxuan Chen Jiangshan Zhang Xuejing Yuan Shengzhi Zhang Kai Chen Xiaofeng Wang Shanqing Guo AAML 42 15 0 19 Mar 2021
A Robust Adversarial Network-Based End-to-End Communications System With Strong Generalization Ability Against Adversarial Attacks Yudi Dong Huaxia Wang Yu-dong Yao AAML GAN 24 5 0 03 Mar 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
Understanding Robustness in Teacher-Student Setting: A New Perspective Zhuolin Yang Zhaoxi Chen Tiffany Cai Xinyun Chen Bo-wen Li Yuandong Tian AAML 35 2 0 25 Feb 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training Vasu Singla Sahil Singla David Jacobs S. Feizi AAML 43 45 0 15 Feb 2021
Universal Adversarial Examples and Perturbations for Quantum Classifiers Weiyuan Gong D. Deng AAML 37 23 0 15 Feb 2021