Towards Evaluating the Robustness of Neural Networks

16 August 2016

Papers citing "Towards Evaluating the Robustness of Neural Networks"

50 / 1,684 papers shown

Title
A Study on the Uncertainty of Convolutional Layers in Deep Neural Networks Hao Shen Sihong Chen Ran Wang 30 5 0 27 Nov 2020
Invisible Perturbations: Physical Adversarial Examples Exploiting the Rolling Shutter Effect Athena Sayles Ashish Hooda M. Gupta Rahul Chatterjee Earlence Fernandes AAML 22 76 0 26 Nov 2020
Probing Model Signal-Awareness via Prediction-Preserving Input Minimization Sahil Suneja Yunhui Zheng Yufan Zhuang Jim Laredo Alessandro Morari AAML 32 33 0 25 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
Learnable Boundary Guided Adversarial Training Jiequan Cui Shu Liu Liwei Wang Jiaya Jia OOD AAML 30 124 0 23 Nov 2020
Adversarial Threats to DeepFake Detection: A Practical Perspective Paarth Neekhara Brian Dolhansky Joanna Bitton Cristian Canton Ferrer AAML 13 79 0 19 Nov 2020
Adversarially Robust Classification based on GLRT Bhagyashree Puranik Upamanyu Madhow Ramtin Pedarsani VLM AAML 23 4 0 16 Nov 2020
Solving Inverse Problems With Deep Neural Networks -- Robustness Included? Martin Genzel Jan Macdonald M. März AAML OOD 37 101 0 09 Nov 2020
A survey on practical adversarial examples for malware classifiers Daniel Park B. Yener AAML 44 14 0 06 Nov 2020
Deep-Dup: An Adversarial Weight Duplication Attack Framework to Crush Deep Neural Network in Multi-Tenant FPGA Adnan Siraj Rakin Yukui Luo Xiaolin Xu Deliang Fan AAML 25 49 0 05 Nov 2020
Detecting Backdoors in Neural Networks Using Novel Feature-Based Anomaly Detection Hao Fu A. Veldanda Prashanth Krishnamurthy S. Garg Farshad Khorrami AAML 35 14 0 04 Nov 2020
Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks Tao Bai Jinqi Luo Jun Zhao AAML 54 8 0 03 Nov 2020
Being Single Has Benefits. Instance Poisoning to Deceive Malware Classifiers T. Shapira David Berend Ishai Rosenberg Yang Liu A. Shabtai Yuval Elovici AAML 27 4 0 30 Oct 2020
Perception Improvement for Free: Exploring Imperceptible Black-box Adversarial Attacks on Image Classification Yongwei Wang Mingquan Feng Rabab Ward Z. J. Wang Lanjun Wang AAML 19 3 0 30 Oct 2020
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable? Anna-Kathrin Kopetzki Bertrand Charpentier Daniel Zügner Sandhya Giri Stephan Günnemann 28 45 0 28 Oct 2020
GreedyFool: Distortion-Aware Sparse Adversarial Attack Xiaoyi Dong Dongdong Chen Jianmin Bao Chuan Qin Lu Yuan Weiming Zhang Nenghai Yu Dong Chen AAML 18 63 0 26 Oct 2020
Robustness May Be at Odds with Fairness: An Empirical Study on Class-wise Accuracy Philipp Benz Chaoning Zhang Adil Karjauv In So Kweon AAML 26 57 0 26 Oct 2020
Dynamic Adversarial Patch for Evading Object Detection Models Shahar Hoory T. Shapira A. Shabtai Yuval Elovici AAML 18 41 0 25 Oct 2020
Generating Plausible Counterfactual Explanations for Deep Transformers in Financial Text Classification Linyi Yang Eoin M. Kenny T. L. J. Ng Yi Yang Barry Smyth Ruihai Dong 15 70 0 23 Oct 2020
Towards Robust Neural Networks via Orthogonal Diversity Kun Fang Qinghua Tao Yingwen Wu Tao Li Jia Cai Feipeng Cai Xiaolin Huang Jie Yang AAML 41 8 0 23 Oct 2020
Adversarial Attacks on Binary Image Recognition Systems Eric Balkanski Harrison W. Chase Kojin Oshiba Alexander Rilee Yaron Singer Richard Wang AAML 47 4 0 22 Oct 2020
Learning Black-Box Attackers with Transferable Priors and Query Feedback Jiancheng Yang Yangzhou Jiang Xiaoyang Huang Bingbing Ni Chenglong Zhao AAML 18 81 0 21 Oct 2020
Boosting Gradient for White-Box Adversarial Attacks Hongying Liu Zhenyu Zhou Fanhua Shang Xiaoyu Qi Yuanyuan Liu L. Jiao AAML 24 7 0 21 Oct 2020
A Survey of Machine Learning Techniques in Adversarial Image Forensics Ehsan Nowroozi Ali Dehghantanha R. Parizi K. Choo AAML 25 72 0 19 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 39 48 0 19 Oct 2020
HABERTOR: An Efficient and Effective Deep Hatespeech Detector T. Tran Yifan Hu Changwei Hu Kevin Yen Fei Tan Kyumin Lee Serim Park VLM 34 32 0 17 Oct 2020
A Generative Model based Adversarial Security of Deep Learning and Linear Classifier Models Ferhat Ozgur Catak Samed Sivaslioglu Kevser Sahinbas AAML 28 7 0 17 Oct 2020
DPAttack: Diffused Patch Attacks against Universal Object Detection Shudeng Wu Tao Dai Shutao Xia AAML 21 26 0 16 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
Reverse Engineering Imperceptible Backdoor Attacks on Deep Neural Networks for Detection and Training Set Cleansing Zhen Xiang David J. Miller G. Kesidis 35 22 0 15 Oct 2020
GreedyFool: Multi-Factor Imperceptibility and Its Application to Designing a Black-box Adversarial Attack Hui Liu Bo Zhao Minzhi Ji Peng Liu AAML 29 6 0 14 Oct 2020
Targeted Physical-World Attention Attack on Deep Learning Models in Road Sign Recognition Xinghao Yang Weifeng Liu Shengli Zhang Wei Liu Dacheng Tao AAML 27 28 0 09 Oct 2020
A Unified Approach to Interpreting and Boosting Adversarial Transferability Xin Eric Wang Jie Ren Shuyu Lin Xiangming Zhu Yisen Wang Quanshi Zhang AAML 29 94 0 08 Oct 2020
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples Sven Gowal Chongli Qin J. Uesato Timothy A. Mann Pushmeet Kohli AAML 22 325 0 07 Oct 2020
Double Targeted Universal Adversarial Perturbations Philipp Benz Chaoning Zhang Tooba Imtiaz In So Kweon AAML 43 48 0 07 Oct 2020
Global Optimization of Objective Functions Represented by ReLU Networks Christopher A. Strong Haoze Wu Aleksandar Zeljić Kyle D. Julian Guy Katz Clark W. Barrett Mykel J. Kochenderfer AAML 17 33 0 07 Oct 2020
Not All Datasets Are Born Equal: On Heterogeneous Data and Adversarial Examples Yael Mathov Eden Levy Ziv Katzir A. Shabtai Yuval Elovici AAML 33 14 0 07 Oct 2020
Geometry-aware Instance-reweighted Adversarial Training Jingfeng Zhang Jianing Zhu Gang Niu Bo Han Masashi Sugiyama Mohan Kankanhalli AAML 47 269 0 05 Oct 2020
An Empirical Study of DNNs Robustification Inefficacy in Protecting Visual Recommenders Vito Walter Anelli Tommaso Di Noia Daniele Malitesta Felice Antonio Merra AAML 27 2 0 02 Oct 2020
Block-wise Image Transformation with Secret Key for Adversarially Robust Defense Maungmaung Aprilpyone Hitoshi Kiya 29 57 0 02 Oct 2020
Adversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated Gradients Yifei Huang Yaodong Yu Hongyang R. Zhang Yi Ma Yuan Yao AAML 37 26 0 28 Sep 2020
Improving Query Efficiency of Black-box Adversarial Attack Yang Bai Yuyuan Zeng Yong Jiang Yisen Wang Shutao Xia Weiwei Guo AAML MLAU 45 52 0 24 Sep 2020
Generating Adversarial yet Inconspicuous Patches with a Single Image Jinqi Luo Tao Bai Jun Zhao AAML 27 6 0 21 Sep 2020
Adversarial Training with Stochastic Weight Average Joong-won Hwang Youngwan Lee Sungchan Oh Yuseok Bae OOD AAML 31 11 0 21 Sep 2020
Bias Field Poses a Threat to DNN-based X-Ray Recognition Binyu Tian Qing Guo Felix Juefei Xu W. L. Chan Yupeng Cheng Xiaohong Li Xiaofei Xie Shengchao Qin AAML AI4CE 36 33 0 19 Sep 2020
Label Smoothing and Adversarial Robustness Chaohao Fu Hongbin Chen Na Ruan Weijia Jia AAML 16 12 0 17 Sep 2020
Light Can Hack Your Face! Black-box Backdoor Attack on Face Recognition Systems Haoliang Li Yufei Wang Xiaofei Xie Yang Liu Shiqi Wang Renjie Wan Lap-Pui Chau City University of Hong Kong AAML 24 32 0 15 Sep 2020
Input Hessian Regularization of Neural Networks Waleed Mustafa Robert A. Vandermeulen Marius Kloft AAML 25 12 0 14 Sep 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 46 62 0 11 Sep 2020
Quantifying the Preferential Direction of the Model Gradient in Adversarial Training With Projected Gradient Descent Ricardo Bigolin Lanfredi Joyce D. Schroeder Tolga Tasdizen 27 11 0 10 Sep 2020