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Enhancing Robustness of Machine Learning Systems via Data Transformations

9 April 2017

Papers citing "Enhancing Robustness of Machine Learning Systems via Data Transformations"

50 / 105 papers shown

Title
REGroup: Rank-aggregating Ensemble of Generative Classifiers for Robust Predictions Lokender Tiwari Anish Madan Saket Anand Subhashis Banerjee AAML 37 1 0 18 Jun 2020
Adversarial Imitation Attack Mingyi Zhou Jing Wu Yipeng Liu Xiaolin Huang Shuaicheng Liu Xiang Zhang Ce Zhu AAML 39 0 0 28 Mar 2020
DaST: Data-free Substitute Training for Adversarial Attacks Mingyi Zhou Jing Wu Yipeng Liu Shuaicheng Liu Ce Zhu 84 145 0 28 Mar 2020
Adversarial Perturbations Prevail in the Y-Channel of the YCbCr Color Space Camilo Pestana Naveed Akhtar Wei Liu D. Glance Ajmal Mian AAML 60 10 0 25 Feb 2020
Ensemble Noise Simulation to Handle Uncertainty about Gradient-based Adversarial Attacks Rehana Mahfuz R. Sahay Aly El Gamal AAML 40 2 0 26 Jan 2020
ATHENA: A Framework based on Diverse Weak Defenses for Building Adversarial Defense Meng Jianhai Su Jason M. O'Kane Pooyan Jamshidi AAML 57 7 0 02 Jan 2020
Using Depth for Pixel-Wise Detection of Adversarial Attacks in Crowd Counting Weizhe Liu Mathieu Salzmann Pascal Fua AAML 75 9 0 26 Nov 2019
A New Defense Against Adversarial Images: Turning a Weakness into a Strength Tao Yu Shengyuan Hu Chuan Guo Wei-Lun Chao Kilian Q. Weinberger AAML 120 103 0 16 Oct 2019
Lower Bounds on Adversarial Robustness from Optimal Transport A. Bhagoji Daniel Cullina Prateek Mittal OOD OT AAML 70 94 0 26 Sep 2019
TBT: Targeted Neural Network Attack with Bit Trojan Adnan Siraj Rakin Zhezhi He Deliang Fan AAML 71 216 0 10 Sep 2019
On Defending Against Label Flipping Attacks on Malware Detection Systems R. Taheri R. Javidan Mohammad Shojafar Zahra Pooranian A. Miri Mauro Conti AAML 85 92 0 13 Aug 2019
MetaAdvDet: Towards Robust Detection of Evolving Adversarial Attacks Chen Ma Chenxu Zhao Hailin Shi Li Chen Junhai Yong Dan Zeng AAML 55 17 0 06 Aug 2019
Random Directional Attack for Fooling Deep Neural Networks Wenjian Luo Chenwang Wu Nan Zhou Li Ni AAML 21 4 0 06 Aug 2019
Adversarial Security Attacks and Perturbations on Machine Learning and Deep Learning Methods Arif Siddiqi AAML 64 11 0 17 Jul 2019
A Computationally Efficient Method for Defending Adversarial Deep Learning Attacks R. Sahay Rehana Mahfuz Aly El Gamal AAML 33 5 0 13 Jun 2019
ML-LOO: Detecting Adversarial Examples with Feature Attribution Puyudi Yang Jianbo Chen Cho-Jui Hsieh Jane-ling Wang Michael I. Jordan AAML 93 101 0 08 Jun 2019
Sample Complexity of Sample Average Approximation for Conditional Stochastic Optimization Yifan Hu Xin Chen Niao He 91 36 0 28 May 2019
Moving Target Defense for Deep Visual Sensing against Adversarial Examples Qun Song Zhenyu Yan Rui Tan AAML 45 20 0 11 May 2019
Better the Devil you Know: An Analysis of Evasion Attacks using Out-of-Distribution Adversarial Examples Vikash Sehwag A. Bhagoji Liwei Song Chawin Sitawarin Daniel Cullina M. Chiang Prateek Mittal OODD 77 26 0 05 May 2019
Malware Evasion Attack and Defense Yonghong Huang Utkarsh Verma Celeste Fralick G. Infante-Lopez B. Kumar Carl Woodward AAML 65 16 0 07 Apr 2019
JumpReLU: A Retrofit Defense Strategy for Adversarial Attacks N. Benjamin Erichson Z. Yao Michael W. Mahoney AAML 69 24 0 07 Apr 2019
Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence Yi Han David Hubczenko Paul Montague O. Vel Tamas Abraham Benjamin I. P. Rubinstein C. Leckie T. Alpcan S. Erfani AAML 54 6 0 25 Feb 2019
Is Spiking Secure? A Comparative Study on the Security Vulnerabilities of Spiking and Deep Neural Networks Alberto Marchisio Giorgio Nanfa Faiq Khalid Muhammad Abdullah Hanif Maurizio Martina Mohamed Bennai AAML 55 7 0 04 Feb 2019
CapsAttacks: Robust and Imperceptible Adversarial Attacks on Capsule Networks Alberto Marchisio Giorgio Nanfa Faiq Khalid Muhammad Abdullah Hanif Maurizio Martina Mohamed Bennai GAN AAML 74 26 0 28 Jan 2019
Exploiting the Inherent Limitation of L0 Adversarial Examples F. Zuo Bokai Yang Xiaopeng Li Lannan Luo Qiang Zeng AAML 47 1 0 23 Dec 2018
Combatting Adversarial Attacks through Denoising and Dimensionality Reduction: A Cascaded Autoencoder Approach R. Sahay Rehana Mahfuz Aly El Gamal 55 34 0 07 Dec 2018
FineFool: Fine Object Contour Attack via Attention Jinyin Chen Haibin Zheng Hui Xiong Mengmeng Su AAML 60 3 0 01 Dec 2018
Intrinsic Geometric Vulnerability of High-Dimensional Artificial Intelligence Luca Bortolussi G. Sanguinetti AAML 51 4 0 08 Nov 2018
Robust Adversarial Learning via Sparsifying Front Ends S. Gopalakrishnan Zhinus Marzi Metehan Cekic Upamanyu Madhow Ramtin Pedarsani AAML 58 3 0 24 Oct 2018
Adversarial Examples - A Complete Characterisation of the Phenomenon A. Serban E. Poll Joost Visser SILM AAML 102 49 0 02 Oct 2018
Defensive Dropout for Hardening Deep Neural Networks under Adversarial Attacks Siyue Wang Tianlin Li Pu Zhao Wujie Wen David Kaeli S. Chin Xinyu Lin AAML 76 70 0 13 Sep 2018
Reinforcement Learning for Autonomous Defence in Software-Defined Networking Yi Han Benjamin I. P. Rubinstein Tamas Abraham T. Alpcan O. Vel S. Erfani David Hubczenko C. Leckie Paul Montague AAML 55 69 0 17 Aug 2018
Mitigation of Adversarial Attacks through Embedded Feature Selection Ziyi Bao Luis Muñoz-González Emil C. Lupu AAML 44 1 0 16 Aug 2018
Motivating the Rules of the Game for Adversarial Example Research Justin Gilmer Ryan P. Adams Ian Goodfellow David G. Andersen George E. Dahl AAML 107 229 0 18 Jul 2018
A New Angle on L2 Regularization T. Tanay Lewis D. Griffin LLMSV 50 5 0 28 Jun 2018
Gradient Similarity: An Explainable Approach to Detect Adversarial Attacks against Deep Learning J. Dhaliwal S. Shintre AAML 49 15 0 27 Jun 2018
Detection based Defense against Adversarial Examples from the Steganalysis Point of View Jiayang Liu Weiming Zhang Yiwei Zhang Dongdong Hou Yujia Liu Hongyue Zha Nenghai Yu AAML 101 100 0 21 Jun 2018
An Explainable Adversarial Robustness Metric for Deep Learning Neural Networks Chirag Agarwal Bo Dong Dan Schonfeld A. Hoogs 50 2 0 05 Jun 2018
PAC-learning in the presence of evasion adversaries Daniel Cullina A. Bhagoji Prateek Mittal AAML 102 55 0 05 Jun 2018
Towards Dependable Deep Convolutional Neural Networks (CNNs) with Out-distribution Learning Mahdieh Abbasi Arezoo Rajabi Christian Gagné R. Bobba OODD 61 6 0 24 Apr 2018
An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks Pu Zhao Sijia Liu Yanzhi Wang Xinyu Lin AAML 72 37 0 09 Apr 2018
Defending against Adversarial Images using Basis Functions Transformations Uri Shaham J. Garritano Yutaro Yamada Ethan Weinberger A. Cloninger Xiuyuan Cheng Kelly P. Stanton Y. Kluger AAML 69 57 0 28 Mar 2018
Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial Examples Zihao Liu Qi Liu Tao Liu Nuo Xu Xue Lin Yanzhi Wang Wujie Wen AAML MQ 85 265 0 14 Mar 2018
Combating Adversarial Attacks Using Sparse Representations S. Gopalakrishnan Zhinus Marzi Upamanyu Madhow Ramtin Pedarsani AAML 69 24 0 11 Mar 2018
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries Z. Yao A. Gholami Qi Lei Kurt Keutzer Michael W. Mahoney 100 167 0 22 Feb 2018
Unravelling Robustness of Deep Learning based Face Recognition Against Adversarial Attacks Gaurav Goswami Nalini Ratha Akshay Agarwal Richa Singh Mayank Vatsa AAML 97 166 0 22 Feb 2018
Shield: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression Nilaksh Das Madhuri Shanbhogue Shang-Tse Chen Fred Hohman Siwei Li Li-Wei Chen Michael E. Kounavis Duen Horng Chau FedML AAML 85 228 0 19 Feb 2018
Divide, Denoise, and Defend against Adversarial Attacks Seyed-Mohsen Moosavi-Dezfooli A. Shrivastava Oncel Tuzel AAML 57 45 0 19 Feb 2018
Sparsity-based Defense against Adversarial Attacks on Linear Classifiers Zhinus Marzi S. Gopalakrishnan Upamanyu Madhow Ramtin Pedarsani AAML 102 31 0 15 Jan 2018
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey Naveed Akhtar Ajmal Mian AAML 146 1,873 0 02 Jan 2018