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
Defending Against Adversarial Examples with K-Nearest Neighbor Chawin Sitawarin David Wagner AAML 11 29 0 23 Jun 2019
A Computationally Efficient Method for Defending Adversarial Deep Learning Attacks R. Sahay Rehana Mahfuz Aly El Gamal AAML 22 5 0 13 Jun 2019
Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks Ziang Yan Yiwen Guo Changshui Zhang AAML 33 110 0 11 Jun 2019
Evaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective Lu Wang Xuanqing Liu Jinfeng Yi Zhi-Hua Zhou Cho-Jui Hsieh AAML 31 22 0 10 Jun 2019
Robustness Verification of Tree-based Models Hongge Chen Huan Zhang Si Si Yang Li Duane S. Boning Cho-Jui Hsieh AAML 22 76 0 10 Jun 2019
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks Maksym Andriushchenko Matthias Hein 28 61 0 08 Jun 2019
ML-LOO: Detecting Adversarial Examples with Feature Attribution Puyudi Yang Jianbo Chen Cho-Jui Hsieh Jane-ling Wang Michael I. Jordan AAML 22 101 0 08 Jun 2019
Robustness for Non-Parametric Classification: A Generic Attack and Defense Yao-Yuan Yang Cyrus Rashtchian Yizhen Wang Kamalika Chaudhuri SILM AAML 34 42 0 07 Jun 2019
Mixed Strategy Game Model Against Data Poisoning Attacks Yi-Tsen Ou Reza Samavi AAML 24 4 0 07 Jun 2019
Multi-way Encoding for Robustness Donghyun Kim Sarah Adel Bargal Jianming Zhang Stan Sclaroff AAML 18 2 0 05 Jun 2019
Adversarial Examples for Edge Detection: They Exist, and They Transfer Christian Cosgrove Alan Yuille AAML GAN 25 12 0 02 Jun 2019
Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward A. Qayyum Muhammad Usama Junaid Qadir Ala I. Al-Fuqaha AAML 27 187 0 29 May 2019
Functional Adversarial Attacks Cassidy Laidlaw S. Feizi AAML 19 183 0 29 May 2019
Snooping Attacks on Deep Reinforcement Learning Matthew J. Inkawhich Yiran Chen Hai Helen Li AAML 22 25 0 28 May 2019
Cross-Domain Transferability of Adversarial Perturbations Muzammal Naseer Salman H. Khan M. H. Khan Fahad Shahbaz Khan Fatih Porikli AAML 33 145 0 28 May 2019
Thwarting finite difference adversarial attacks with output randomization Haidar Khan Daniel Park Azer Khan B. Yener SILM AAML 41 0 0 23 May 2019
Biometric Backdoors: A Poisoning Attack Against Unsupervised Template Updating Giulio Lovisotto Simon Eberz Ivan Martinovic AAML 21 35 0 22 May 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
Percival: Making In-Browser Perceptual Ad Blocking Practical With Deep Learning Z. Din P. Tigas Samuel T. King B. Livshits VLM 39 29 0 17 May 2019
Salient Object Detection in the Deep Learning Era: An In-Depth Survey Wenguan Wang Qiuxia Lai Huazhu Fu Jianbing Shen Haibin Ling Ruigang Yang 43 610 0 19 Apr 2019
Curls & Whey: Boosting Black-Box Adversarial Attacks Yucheng Shi Siyu Wang Yahong Han AAML 18 116 0 02 Apr 2019
On the Vulnerability of CNN Classifiers in EEG-Based BCIs Xiao Zhang Dongrui Wu AAML 24 82 0 31 Mar 2019
Smart Home Personal Assistants: A Security and Privacy Review Jide S. Edu Jose Such Guillermo Suarez-Tangil 14 92 0 13 Mar 2019
Neural Network Model Extraction Attacks in Edge Devices by Hearing Architectural Hints Xing Hu Ling Liang Lei Deng Shuangchen Li Xinfeng Xie Yu Ji Yufei Ding Chang Liu T. Sherwood Yuan Xie AAML MLAU 23 36 0 10 Mar 2019
Detecting Overfitting via Adversarial Examples Roman Werpachowski András Gyorgy Csaba Szepesvári TDI 26 45 0 06 Mar 2019
Copying Machine Learning Classifiers Irene Unceta Jordi Nin O. Pujol 14 18 0 05 Mar 2019
Adversarial Attacks on Time Series Fazle Karim Somshubra Majumdar H. Darabi AI4TS 23 97 0 27 Feb 2019
The Best Defense Is a Good Offense: Adversarial Attacks to Avoid Modulation Detection Muhammad Zaid Hameed András Gyorgy Deniz Gunduz AAML 21 72 0 27 Feb 2019
Robust Decision Trees Against Adversarial Examples Hongge Chen Huan Zhang Duane S. Boning Cho-Jui Hsieh AAML 31 116 0 27 Feb 2019
Verification of Non-Linear Specifications for Neural Networks Chongli Qin Krishnamurthy Dvijotham Dvijotham Brendan O'Donoghue Rudy Bunel Robert Stanforth Sven Gowal J. Uesato G. Swirszcz Pushmeet Kohli AAML 16 43 0 25 Feb 2019
MaskDGA: A Black-box Evasion Technique Against DGA Classifiers and Adversarial Defenses Lior Sidi Asaf Nadler A. Shabtai AAML 31 22 0 24 Feb 2019
Physical Adversarial Attacks Against End-to-End Autoencoder Communication Systems Meysam Sadeghi Erik G. Larsson AAML 22 112 0 22 Feb 2019
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples Kevin Roth Yannic Kilcher Thomas Hofmann AAML 27 175 0 13 Feb 2019
Weighted-Sampling Audio Adversarial Example Attack Xiaolei Liu Xiaosong Zhang Kun Wan Qingxin Zhu Yufei Ding DiffM AAML 36 36 0 26 Jan 2019
ECGadv: Generating Adversarial Electrocardiogram to Misguide Arrhythmia Classification System Huangxun Chen Chenyu Huang Qianyi Huang Qian Zhang Wei Wang AAML 31 26 0 12 Jan 2019
A Multiversion Programming Inspired Approach to Detecting Audio Adversarial Examples Qiang Zeng Jianhai Su Chenglong Fu Golam Kayas Lannan Luo AAML 27 46 0 26 Dec 2018
Defense-VAE: A Fast and Accurate Defense against Adversarial Attacks Xiang Li Shihao Ji AAML 27 26 0 17 Dec 2018
Adversarial Framing for Image and Video Classification Konrad Zolna Michal Zajac Negar Rostamzadeh Pedro H. O. Pinheiro AAML 30 60 0 11 Dec 2018
On the Security of Randomized Defenses Against Adversarial Samples K. Sharad G. Marson H. Truong Ghassan O. Karame AAML 35 1 0 11 Dec 2018
Learning Transferable Adversarial Examples via Ghost Networks Yingwei Li S. Bai Yuyin Zhou Cihang Xie Zhishuai Zhang Alan Yuille AAML 42 136 0 09 Dec 2018
AutoGAN: Robust Classifier Against Adversarial Attacks Blerta Lindqvist Shridatt Sugrim R. Izmailov AAML 29 7 0 08 Dec 2018
Interpretable Deep Learning under Fire Xinyang Zhang Ningfei Wang Hua Shen S. Ji Xiapu Luo Ting Wang AAML AI4CE 30 169 0 03 Dec 2018
Noisy Computations during Inference: Harmful or Helpful? Minghai Qin D. Vučinić AAML 19 5 0 26 Nov 2018
A Spectral View of Adversarially Robust Features Shivam Garg Vatsal Sharan B. Zhang Gregory Valiant AAML 19 21 0 15 Nov 2018
Mathematical Analysis of Adversarial Attacks Zehao Dou Stanley J. Osher Bao Wang AAML 24 18 0 15 Nov 2018
Stronger Data Poisoning Attacks Break Data Sanitization Defenses Pang Wei Koh Jacob Steinhardt Percy Liang 6 240 0 02 Nov 2018
Attack Graph Convolutional Networks by Adding Fake Nodes Xiaoyun Wang Minhao Cheng Joe Eaton Cho-Jui Hsieh S. F. Wu AAML GNN 33 78 0 25 Oct 2018
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
Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks Kenneth T. Co Luis Muñoz-González Sixte de Maupeou Emil C. Lupu AAML 22 67 0 30 Sep 2018
To compress or not to compress: Understanding the Interactions between Adversarial Attacks and Neural Network Compression Yiren Zhao Ilia Shumailov Robert D. Mullins Ross J. Anderson AAML 11 43 0 29 Sep 2018