Title
An Empirical Study of Accuracy, Fairness, Explainability, Distributional Robustness, and Adversarial Robustness Moninder Singh Gevorg Ghalachyan Kush R. Varshney R. Bryant 24 9 0 29 Sep 2021
MUTEN: Boosting Gradient-Based Adversarial Attacks via Mutant-Based Ensembles Yuejun Guo Qiang Hu Maxime Cordy Michail Papadakis Yves Le Traon AAML 32 2 0 27 Sep 2021
Automated Robustness with Adversarial Training as a Post-Processing Step Ambrish Rawat M. Sinn Beat Buesser AAML 19 0 0 06 Sep 2021
SEC4SR: A Security Analysis Platform for Speaker Recognition Guangke Chen Zhe Zhao Fu Song Sen Chen Lingling Fan Yang Liu AAML 32 12 0 04 Sep 2021
The Threat of Offensive AI to Organizations Yisroel Mirsky Ambra Demontis J. Kotak Ram Shankar Deng Gelei Liu Yang Xinming Zhang Wenke Lee Yuval Elovici Battista Biggio 38 81 0 30 Jun 2021
Stochastic-Shield: A Probabilistic Approach Towards Training-Free Adversarial Defense in Quantized CNNs Lorena Qendro Sangwon Ha R. D. Jong Partha P. Maji AAML FedML MQ 21 7 0 13 May 2021
Performance Evaluation of Adversarial Attacks: Discrepancies and Solutions Jing Wu Mingyi Zhou Ce Zhu Yipeng Liu Mehrtash Harandi Li Li AAML 57 10 0 22 Apr 2021
Rethinking Image-Scaling Attacks: The Interplay Between Vulnerabilities in Machine Learning Systems Yue Gao Ilia Shumailov Kassem Fawaz AAML 34 10 0 18 Apr 2021
Multiplicative Reweighting for Robust Neural Network Optimization Noga Bar Tomer Koren Raja Giryes OOD NoLa 18 9 0 24 Feb 2021
Cortical Features for Defense Against Adversarial Audio Attacks Ilya Kavalerov Frank Zheng W. Czaja Ramalingam Chellappa AAML 27 0 0 30 Jan 2021
Adversarial Attacks for Tabular Data: Application to Fraud Detection and Imbalanced Data F. Cartella Orlando Anunciação Yuki Funabiki D. Yamaguchi Toru Akishita Olivier Elshocht AAML 65 71 0 20 Jan 2021
DeepSweep: An Evaluation Framework for Mitigating DNN Backdoor Attacks using Data Augmentation Han Qiu Yi Zeng Shangwei Guo Tianwei Zhang Meikang Qiu B. Thuraisingham AAML 24 191 0 13 Dec 2020
Interpretable Graph Capsule Networks for Object Recognition Jindong Gu Volker Tresp FAtt 19 36 0 03 Dec 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 234 681 0 19 Oct 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
Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review Yansong Gao Bao Gia Doan Zhi-Li Zhang Siqi Ma Jiliang Zhang Anmin Fu Surya Nepal Hyoungshick Kim AAML 36 221 0 21 Jul 2020
A Survey on Security Attacks and Defense Techniques for Connected and Autonomous Vehicles M. Pham Kaiqi Xiong 25 138 0 16 Jul 2020
Evaluation of Adversarial Training on Different Types of Neural Networks in Deep Learning-based IDSs Rana Abou-Khamis Ashraf Matrawy AAML 41 46 0 08 Jul 2020
Tricking Adversarial Attacks To Fail Blerta Lindqvist AAML 16 0 0 08 Jun 2020
Adversarial Attacks on Classifiers for Eye-based User Modelling Inken Hagestedt Michael Backes Andreas Bulling AAML 24 6 0 01 Jun 2020
Vulnerability of deep neural networks for detecting COVID-19 cases from chest X-ray images to universal adversarial attacks Hokuto Hirano K. Koga Kazuhiro Takemoto AAML 27 47 0 22 May 2020
Utilizing Network Properties to Detect Erroneous Inputs Matt Gorbett Nathaniel Blanchard AAML 23 6 0 28 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
Advbox: a toolbox to generate adversarial examples that fool neural networks Dou Goodman Xin Hao Yang Wang Yuesheng Wu Junfeng Xiong Huan Zhang AAML 15 53 0 13 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
Benchmarking Adversarial Robustness Yinpeng Dong Qi-An Fu Xiao Yang Tianyu Pang Hang Su Zihao Xiao Jun Zhu AAML 31 36 0 26 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
Simple iterative method for generating targeted universal adversarial perturbations Hokuto Hirano Kazuhiro Takemoto AAML 33 30 0 15 Nov 2019
When Explainability Meets Adversarial Learning: Detecting Adversarial Examples using SHAP Signatures Gil Fidel Ron Bitton A. Shabtai FAtt GAN 21 119 0 08 Sep 2019
Improved Adversarial Robustness by Reducing Open Space Risk via Tent Activations Andras Rozsa Terrance E. Boult AAML 30 18 0 07 Aug 2019
Optimization Problems for Machine Learning: A Survey Claudio Gambella Bissan Ghaddar Joe Naoum-Sawaya AI4CE 37 178 0 16 Jan 2019
Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering Bryant Chen Wilka Carvalho Wenjie Li Heiko Ludwig Benjamin Edwards Chengyao Chen Ziqiang Cao Biplav Srivastava AAML 29 782 0 09 Nov 2018
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 303 3,115 0 04 Nov 2016