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
Spanning Attack: Reinforce Black-box Attacks with Unlabeled Data Lu Wang Huan Zhang Jinfeng Yi Cho-Jui Hsieh Yuan Jiang AAML 35 12 0 11 May 2020
Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness Pu Zhao Pin-Yu Chen Payel Das Karthikeyan N. Ramamurthy Xue Lin AAML 64 185 0 30 Apr 2020
Imitation Attacks and Defenses for Black-box Machine Translation Systems Eric Wallace Mitchell Stern D. Song AAML 27 120 0 30 Apr 2020
Transferable Perturbations of Deep Feature Distributions Nathan Inkawhich Kevin J Liang Lawrence Carin Yiran Chen AAML 30 84 0 27 Apr 2020
Adversarial Attacks and Defenses: An Interpretation Perspective Ninghao Liu Mengnan Du Ruocheng Guo Huan Liu Xia Hu AAML 31 8 0 23 Apr 2020
PatchAttack: A Black-box Texture-based Attack with Reinforcement Learning Chenglin Yang Adam Kortylewski Cihang Xie Yinzhi Cao Alan Yuille AAML 45 109 0 12 Apr 2020
PoisHygiene: Detecting and Mitigating Poisoning Attacks in Neural Networks Junfeng Guo Zelun Kong Cong Liu AAML 32 1 0 24 Mar 2020
Adversarial Perturbations Fool Deepfake Detectors Apurva Gandhi Shomik Jain AAML 16 103 0 24 Mar 2020
Face-Off: Adversarial Face Obfuscation Varun Chandrasekaran Chuhan Gao Brian Tang Kassem Fawaz S. Jha Suman Banerjee PICV 27 44 0 19 Mar 2020
Diversity can be Transferred: Output Diversification for White- and Black-box Attacks Y. Tashiro Yang Song Stefano Ermon AAML 14 13 0 15 Mar 2020
MAB-Malware: A Reinforcement Learning Framework for Attacking Static Malware Classifiers Wei Song Xuezixiang Li Sadia Afroz D. Garg Dmitry Kuznetsov Heng Yin AAML 53 27 0 06 Mar 2020
Towards Practical Lottery Ticket Hypothesis for Adversarial Training Bai Li Shiqi Wang Yunhan Jia Yantao Lu Zhenyu Zhong Lawrence Carin Suman Jana AAML 31 14 0 06 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 72 63 0 02 Mar 2020
On Isometry Robustness of Deep 3D Point Cloud Models under Adversarial Attacks Yue Zhao Yuwei Wu Caihua Chen A. Lim 3DPC 16 70 0 27 Feb 2020
Entangled Watermarks as a Defense against Model Extraction Hengrui Jia Christopher A. Choquette-Choo Varun Chandrasekaran Nicolas Papernot WaLM AAML 13 218 0 27 Feb 2020
Adversarial Ranking Attack and Defense Mo Zhou Zhenxing Niu Le Wang Qilin Zhang G. Hua 36 38 0 26 Feb 2020
Real-Time Detectors for Digital and Physical Adversarial Inputs to Perception Systems Y. Kantaros Taylor J. Carpenter Kaustubh Sridhar Yahan Yang Insup Lee James Weimer AAML 17 12 0 23 Feb 2020
Temporal Sparse Adversarial Attack on Sequence-based Gait Recognition Ziwen He Wei Wang Jing Dong Tieniu Tan AAML 22 23 0 22 Feb 2020
On Adaptive Attacks to Adversarial Example Defenses Florian Tramèr Nicholas Carlini Wieland Brendel A. Madry AAML 109 823 0 19 Feb 2020
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence S. Raschka Joshua Patterson Corey J. Nolet AI4CE 29 485 0 12 Feb 2020
Attacking Optical Character Recognition (OCR) Systems with Adversarial Watermarks Lu Chen Wenyuan Xu AAML 24 21 0 08 Feb 2020
Over-the-Air Adversarial Attacks on Deep Learning Based Modulation Classifier over Wireless Channels Brian Kim Y. Sagduyu Kemal Davaslioglu T. Erpek S. Ulukus AAML 48 68 0 05 Feb 2020
Minimax Defense against Gradient-based Adversarial Attacks Blerta Lindqvist R. Izmailov AAML 19 0 0 04 Feb 2020
Adversarial Machine Learning -- Industry Perspectives Ramnath Kumar Magnus Nyström J. Lambert Andrew Marshall Mario Goertzel Andi Comissoneru Matt Swann Sharon Xia AAML SILM 29 232 0 04 Feb 2020
Towards Sharper First-Order Adversary with Quantized Gradients Zhuanghua Liu Ivor W. Tsang AAML 22 0 0 01 Feb 2020
GhostImage: Remote Perception Attacks against Camera-based Image Classification Systems Yanmao Man Ming Li Ryan M. Gerdes AAML 22 8 0 21 Jan 2020
Universal Adversarial Attack on Attention and the Resulting Dataset DAmageNet Sizhe Chen Zhengbao He Chengjin Sun Jie Yang Xiaolin Huang AAML 31 104 0 16 Jan 2020
Efficient Adversarial Training with Transferable Adversarial Examples Haizhong Zheng Ziqi Zhang Juncheng Gu Honglak Lee A. Prakash AAML 24 108 0 27 Dec 2019
Label-Consistent Backdoor Attacks Alexander Turner Dimitris Tsipras A. Madry AAML 11 383 0 05 Dec 2019
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples Nils Lukas Yuxuan Zhang Florian Kerschbaum MLAU FedML AAML 39 145 0 02 Dec 2019
DeepSmartFuzzer: Reward Guided Test Generation For Deep Learning Samet Demir Hasan Ferit Eniser A. Sen AAML 11 28 0 24 Nov 2019
Enhancing Cross-task Black-Box Transferability of Adversarial Examples with Dispersion Reduction Yantao Lu Yunhan Jia Jianyu Wang Bai Li Weiheng Chai Lawrence Carin Senem Velipasalar AAML 24 81 0 22 Nov 2019
Defective Convolutional Networks Tiange Luo Tianle Cai Mengxiao Zhang Siyu Chen Di He Liwei Wang AAML 35 3 0 19 Nov 2019
Privacy Leakage Avoidance with Switching Ensembles R. Izmailov Peter Lin Chris Mesterharm S. Basu 25 2 0 18 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 21 104 0 13 Nov 2019
Patch augmentation: Towards efficient decision boundaries for neural networks Marcus D. Bloice P. Roth Andreas Holzinger AAML 18 2 0 08 Nov 2019
White-Box Target Attack for EEG-Based BCI Regression Problems Lubin Meng Chin-Teng Lin T. Jung Dongrui Wu AAML 31 42 0 07 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 39 68 0 06 Nov 2019
Towards Robust and Stable Deep Learning Algorithms for Forward Backward Stochastic Differential Equations Batuhan Güler Alexis Laignelet P. Parpas OOD 21 16 0 25 Oct 2019
Effectiveness of random deep feature selection for securing image manipulation detectors against adversarial examples Mauro Barni Ehsan Nowroozi B. Tondi Bowen Zhang AAML 16 17 0 25 Oct 2019
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks Sekitoshi Kanai Yasutoshi Ida Yasuhiro Fujiwara Masanori Yamada S. Adachi AAML 23 1 0 19 Sep 2019
Metric Learning for Adversarial Robustness Chengzhi Mao Ziyuan Zhong Junfeng Yang Carl Vondrick Baishakhi Ray OOD 27 184 0 03 Sep 2019
advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Zhibo Wang Siyan Zheng Mengkai Song Qian Wang Alireza Rahimpour Hairong Qi AAML OOD 19 59 0 25 Aug 2019
Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks Ka-Ho Chow Wenqi Wei Yanzhao Wu Ling Liu AAML 25 15 0 21 Aug 2019
DAPAS : Denoising Autoencoder to Prevent Adversarial attack in Semantic Segmentation Seungju Cho Tae Joon Jun Byungsoo Oh Daeyoung Kim 27 31 0 14 Aug 2019
BlurNet: Defense by Filtering the Feature Maps Ravi Raju Mikko H. Lipasti AAML 42 15 0 06 Aug 2019
Imperio: Robust Over-the-Air Adversarial Examples for Automatic Speech Recognition Systems Lea Schonherr Thorsten Eisenhofer Steffen Zeiler Thorsten Holz D. Kolossa AAML 54 63 0 05 Aug 2019
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
Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks Tribhuvanesh Orekondy Bernt Schiele Mario Fritz AAML 19 164 0 26 Jun 2019
Quantitative Verification of Neural Networks And its Security Applications Teodora Baluta Shiqi Shen Shweta Shinde Kuldeep S. Meel P. Saxena AAML 24 104 0 25 Jun 2019