Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong

15 June 2017

Papers citing "Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong"

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Title
Evaluating the Robustness of Off-Road Autonomous Driving Segmentation against Adversarial Attacks: A Dataset-Centric analysis Pankaj Deoli Rohit Kumar A. Vierling Karsten Berns 83 3 0 03 Feb 2024
Refutation of Shapley Values for XAI -- Additional Evidence Xuanxiang Huang Sasha Rubin AAML 29 4 0 30 Sep 2023
Differential Analysis of Triggers and Benign Features for Black-Box DNN Backdoor Detection Hao Fu Prashanth Krishnamurthy S. Garg Farshad Khorrami AAML 28 13 0 11 Jul 2023
Computational Asymmetries in Robust Classification Samuele Marro M. Lombardi AAML 21 0 0 25 Jun 2023
Detection of Adversarial Physical Attacks in Time-Series Image Data Ramneet Kaur Y. Kantaros Wenwen Si James Weimer Insup Lee AAML 21 3 0 27 Apr 2023
Improved Robustness Against Adaptive Attacks With Ensembles and Error-Correcting Output Codes Thomas Philippon Christian Gagné AAML 28 0 0 04 Mar 2023
Effectiveness of Moving Target Defenses for Adversarial Attacks in ML-based Malware Detection Aqib Rashid Jose Such AAML 23 2 0 01 Feb 2023
Adversarial Detection by Approximation of Ensemble Boundary T. Windeatt AAML 26 0 0 18 Nov 2022
Robust Few-shot Learning Without Using any Adversarial Samples Gaurav Kumar Nayak Ruchit Rawal Inder Khatri Anirban Chakraborty AAML 27 2 0 03 Nov 2022
Data-free Defense of Black Box Models Against Adversarial Attacks Gaurav Kumar Nayak Inder Khatri Ruchit Rawal Anirban Chakraborty AAML 33 1 0 03 Nov 2022
Ares: A System-Oriented Wargame Framework for Adversarial ML Farhan Ahmed Pratik Vaishnavi Kevin Eykholt Amir Rahmati AAML 23 7 0 24 Oct 2022
Hindering Adversarial Attacks with Implicit Neural Representations Andrei A. Rusu D. A. Calian Sven Gowal R. Hadsell AAML 131 4 0 22 Oct 2022
A Perturbation Resistant Transformation and Classification System for Deep Neural Networks Nathaniel R. Dean D. Sarkar AAML 11 0 0 25 Aug 2022
How many perturbations break this model? Evaluating robustness beyond adversarial accuracy R. Olivier Bhiksha Raj AAML 34 5 0 08 Jul 2022
Morphence-2.0: Evasion-Resilient Moving Target Defense Powered by Out-of-Distribution Detection Abderrahmen Amich Ata Kaboudi Birhanu Eshete AAML OODD 20 1 0 15 Jun 2022
Sardino: Ultra-Fast Dynamic Ensemble for Secure Visual Sensing at Mobile Edge Qun Song Zhenyu Yan W. Luo Rui Tan AAML 25 2 0 18 Apr 2022
On the benefits of knowledge distillation for adversarial robustness Javier Maroto Guillermo Ortiz-Jiménez P. Frossard AAML FedML 25 20 0 14 Mar 2022
Enhancing Adversarial Robustness for Deep Metric Learning Mo Zhou Vishal M. Patel AAML 30 18 0 02 Mar 2022
Rethinking Machine Learning Robustness via its Link with the Out-of-Distribution Problem Abderrahmen Amich Birhanu Eshete OOD 18 4 0 18 Feb 2022
What You See is Not What the Network Infers: Detecting Adversarial Examples Based on Semantic Contradiction Yijun Yang Ruiyuan Gao Yu Li Qiuxia Lai Qiang Xu GAN AAML 34 20 0 24 Jan 2022
The Security of Deep Learning Defences for Medical Imaging Mosh Levy Guy Amit Yuval Elovici Yisroel Mirsky AAML MedIm 41 9 0 21 Jan 2022
Frequency Centric Defense Mechanisms against Adversarial Examples Sanket B. Shah Param Raval Harin Khakhi M. Raval AAML 19 7 0 26 Oct 2021
Tensor Normalization and Full Distribution Training Wolfgang Fuhl OOD 23 4 0 06 Sep 2021
On the Importance of Encrypting Deep Features Xingyang Ni H. Huttunen Esa Rahtu MIACV 22 0 0 16 Aug 2021
Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them Florian Tramèr AAML 30 65 0 24 Jul 2021
Controlled Caption Generation for Images Through Adversarial Attacks Nayyer Aafaq Naveed Akhtar Wei Liu M. Shah Ajmal Mian AAML 35 9 0 07 Jul 2021
Who is Responsible for Adversarial Defense? Kishor Datta Gupta D. Dasgupta AAML 27 2 0 27 Jun 2021
DeepMoM: Robust Deep Learning With Median-of-Means Shih-Ting Huang Johannes Lederer FedML 26 6 0 28 May 2021
Dynamic Defense Approach for Adversarial Robustness in Deep Neural Networks via Stochastic Ensemble Smoothed Model Ruoxi Qin Linyuan Wang Xing-yuan Chen Xuehui Du Bin Yan AAML 30 5 0 06 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 24 2 0 02 May 2021
On the robustness of randomized classifiers to adversarial examples Rafael Pinot Laurent Meunier Florian Yger Cédric Gouy-Pailler Y. Chevaleyre Jamal Atif AAML 34 14 0 22 Feb 2021
Security and Privacy for Artificial Intelligence: Opportunities and Challenges Ayodeji Oseni Nour Moustafa Helge Janicke Peng Liu Z. Tari A. Vasilakos AAML 34 48 0 09 Feb 2021
Amata: An Annealing Mechanism for Adversarial Training Acceleration Nanyang Ye Qianxiao Li Xiao-Yun Zhou Zhanxing Zhu AAML 32 15 0 15 Dec 2020
Voting based ensemble improves robustness of defensive models Devvrit Minhao Cheng Cho-Jui Hsieh Inderjit Dhillon OOD FedML AAML 38 12 0 28 Nov 2020
Omni: Automated Ensemble with Unexpected Models against Adversarial Evasion Attack Rui Shu Tianpei Xia Laurie A. Williams Tim Menzies AAML 32 15 0 23 Nov 2020
Detecting Backdoors in Neural Networks Using Novel Feature-Based Anomaly Detection Hao Fu A. Veldanda Prashanth Krishnamurthy S. Garg Farshad Khorrami AAML 33 14 0 04 Nov 2020
Where Does the Robustness Come from? A Study of the Transformation-based Ensemble Defence Chang Liao Yao Cheng Chengfang Fang Jie Shi 23 1 0 28 Sep 2020
Robust Deep Learning Ensemble against Deception Wenqi Wei Ling Liu AAML 39 29 0 14 Sep 2020
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective G. R. Machado Eugênio Silva R. Goldschmidt AAML 33 156 0 08 Sep 2020
TREND: Transferability based Robust ENsemble Design Deepak Ravikumar Sangamesh Kodge Isha Garg Kaushik Roy OOD AAML 21 4 0 04 Aug 2020
Adversarial Attacks against Neural Networks in Audio Domain: Exploiting Principal Components Ken Alparslan Yigit Can Alparslan Matthew Burlick AAML 21 8 0 14 Jul 2020
How benign is benign overfitting? Amartya Sanyal P. Dokania Varun Kanade Philip Torr NoLa AAML 23 57 0 08 Jul 2020
Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain Ishai Rosenberg A. Shabtai Yuval Elovici Lior Rokach AAML 31 12 0 05 Jul 2020
Determining Sequence of Image Processing Technique (IPT) to Detect Adversarial Attacks Kishor Datta Gupta Zahid Akhtar D. Dasgupta AAML 27 9 0 01 Jul 2020
Biologically Inspired Mechanisms for Adversarial Robustness M. V. Reddy Andrzej Banburski Nishka Pant T. Poggio AAML 18 46 0 29 Jun 2020
Blacklight: Scalable Defense for Neural Networks against Query-Based Black-Box Attacks Huiying Li Shawn Shan Emily Wenger Jiayun Zhang Haitao Zheng Ben Y. Zhao AAML 23 42 0 24 Jun 2020
Beware the Black-Box: on the Robustness of Recent Defenses to Adversarial Examples Kaleel Mahmood Deniz Gurevin Marten van Dijk Phuong Ha Nguyen AAML 17 22 0 18 Jun 2020
Toward Adversarial Robustness by Diversity in an Ensemble of Specialized Deep Neural Networks Mahdieh Abbasi Arezoo Rajabi Christian Gagné R. Bobba AAML 14 15 0 17 May 2020
Towards Understanding the Adversarial Vulnerability of Skeleton-based Action Recognition Tianhang Zheng Sheng Liu Changyou Chen Junsong Yuan Baochun Li K. Ren AAML 21 17 0 14 May 2020
EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness against Adversarial Attacks Sanchari Sen Balaraman Ravindran A. Raghunathan FedML AAML 15 63 0 21 Apr 2020