Enhancing Robustness of Machine Learning Systems via Data Transformations

9 April 2017

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

35 / 35 papers shown

Title
A Brain-Inspired Regularizer for Adversarial Robustness Elie Attias Cengiz Pehlevan D. Obeid AAML OOD 20 0 0 04 Oct 2024
Understanding Deep Learning defenses Against Adversarial Examples Through Visualizations for Dynamic Risk Assessment Xabier Echeberria-Barrio Amaia Gil-Lerchundi Jon Egana-Zubia Raul Orduna Urrutia AAML 37 6 0 12 Feb 2024
Boosting Robustness Verification of Semantic Feature Neighborhoods Anan Kabaha Dana Drachsler-Cohen AAML 34 6 0 12 Sep 2022
Data Synthesis for Testing Black-Box Machine Learning Models Diptikalyan Saha Aniya Aggarwal Sandeep Hans 25 4 0 03 Nov 2021
Robust lEarned Shrinkage-Thresholding (REST): Robust unrolling for sparse recover Wei Pu Chao Zhou Yonina C. Eldar M. Rodrigues OOD 21 1 0 20 Oct 2021
Morphence: Moving Target Defense Against Adversarial Examples Abderrahmen Amich Birhanu Eshete AAML 34 24 0 31 Aug 2021
NetFense: Adversarial Defenses against Privacy Attacks on Neural Networks for Graph Data I-Chung Hsieh Cheng-Te Li AAML 25 23 0 22 Jun 2021
Sparta: Spatially Attentive and Adversarially Robust Activation Qing Guo Felix Juefei Xu Changqing Zhou Wei Feng Yang Liu Song Wang AAML 38 4 0 18 May 2021
Mitigating Gradient-based Adversarial Attacks via Denoising and Compression Rehana Mahfuz R. Sahay Aly El Gamal AAML 14 3 0 03 Apr 2021
Automatic Open-World Reliability Assessment Mohsen Jafarzadeh T. Ahmad A. Dhamija Chunchun Li Steve Cruz Terrance E. Boult 26 11 0 11 Nov 2020
Blockchain based Attack Detection on Machine Learning Algorithms for IoT based E-Health Applications Thippa Reddy Gadekallu Manoj M K Sivarama Krishnan S Neeraj Kumar S. Hakak S. Bhattacharya OOD 24 54 0 03 Nov 2020
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 Machine Learning in Image Classification: A Survey Towards the Defender's Perspective G. R. Machado Eugênio Silva R. Goldschmidt AAML 33 157 0 08 Sep 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 29 73 0 07 Aug 2020
Deep Learning Defenses Against Adversarial Examples for Dynamic Risk Assessment Xabier Echeberria-Barrio Amaia Gil-Lerchundi Ines Goicoechea-Telleria Raul Orduna Urrutia AAML 22 5 0 02 Jul 2020
ConFoc: Content-Focus Protection Against Trojan Attacks on Neural Networks Miguel Villarreal-Vasquez B. Bhargava AAML 19 38 0 01 Jul 2020
DaST: Data-free Substitute Training for Adversarial Attacks Mingyi Zhou Jing Wu Yipeng Liu Shuaicheng Liu Ce Zhu 25 142 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 29 10 0 25 Feb 2020
Using Depth for Pixel-Wise Detection of Adversarial Attacks in Crowd Counting Weizhe Liu Mathieu Salzmann Pascal Fua AAML 27 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 58 101 0 16 Oct 2019
On Defending Against Label Flipping Attacks on Malware Detection Systems R. Taheri R. Javidan Mohammad Shojafar Zahra Pooranian A. Miri Mauro Conti AAML 21 88 0 13 Aug 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
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
CapsAttacks: Robust and Imperceptible Adversarial Attacks on Capsule Networks Alberto Marchisio Giorgio Nanfa Faiq Khalid Muhammad Abdullah Hanif Maurizio Martina Mohamed Bennai GAN AAML 22 26 0 28 Jan 2019
Combatting Adversarial Attacks through Denoising and Dimensionality Reduction: A Cascaded Autoencoder Approach R. Sahay Rehana Mahfuz Aly El Gamal 22 33 0 07 Dec 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 50 226 0 18 Jul 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 25 99 0 21 Jun 2018
Towards Dependable Deep Convolutional Neural Networks (CNNs) with Out-distribution Learning Mahdieh Abbasi Arezoo Rajabi Christian Gagné R. Bobba OODD 30 6 0 24 Apr 2018
An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks Pu Zhao Sijia Liu Yanzhi Wang X. Lin AAML 20 37 0 09 Apr 2018
Unravelling Robustness of Deep Learning based Face Recognition Against Adversarial Attacks Gaurav Goswami Nalini Ratha Akshay Agarwal Richa Singh Mayank Vatsa AAML 21 165 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 45 225 0 19 Feb 2018
Detecting Adversarial Attacks on Neural Network Policies with Visual Foresight Yen-Chen Lin Ming Liu Min Sun Jia-Bin Huang AAML 29 48 0 02 Oct 2017
Detecting Adversarial Image Examples in Deep Networks with Adaptive Noise Reduction Bin Liang Hongcheng Li Miaoqiang Su Xirong Li Wenchang Shi Xiaofeng Wang AAML 14 215 0 23 May 2017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks Weilin Xu David Evans Yanjun Qi AAML 25 1,237 0 04 Apr 2017
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 326 5,847 0 08 Jul 2016