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Towards Evaluating the Robustness of Neural Networks

16 August 2016

Papers citing "Towards Evaluating the Robustness of Neural Networks"

50 / 4,017 papers shown

Title
"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice Giovanni Apruzzese Hyrum S. Anderson Savino Dambra D. Freeman Fabio Pierazzi Kevin A. Roundy AAML 112 81 0 29 Dec 2022
How Do Deepfakes Move? Motion Magnification for Deepfake Source Detection U. Ciftci Ilke Demir 67 6 0 28 Dec 2022
Differentiable Search of Accurate and Robust Architectures Yuwei Ou Xiangning Xie Shan Gao Yanan Sun Kay Chen Tan Jiancheng Lv OOD AAML 73 2 0 28 Dec 2022
Publishing Efficient On-device Models Increases Adversarial Vulnerability Sanghyun Hong Nicholas Carlini Alexey Kurakin AAML 77 3 0 28 Dec 2022
MVTN: Learning Multi-View Transformations for 3D Understanding Abdullah Hamdi Faisal AlZahrani Silvio Giancola Guohao Li 3DV 3DPC 143 6 0 27 Dec 2022
Frequency Regularization for Improving Adversarial Robustness Binxiao Huang Chaofan Tao R. Lin Ngai Wong AAML 39 4 0 24 Dec 2022
Out-of-Distribution Detection with Reconstruction Error and Typicality-based Penalty Genki Osada Tsubasa Takahashi Budrul Ahsan Takashi Nishide OODD 98 14 0 24 Dec 2022
Aliasing is a Driver of Adversarial Attacks Adrian Rodriguez-Munoz Antonio Torralba AAML 66 0 0 22 Dec 2022
A Theoretical Study of The Effects of Adversarial Attacks on Sparse Regression Deepak Maurya Jean Honorio AAML 76 0 0 21 Dec 2022
Revisiting Residual Networks for Adversarial Robustness: An Architectural Perspective Shihua Huang Zhichao Lu Kalyanmoy Deb Vishnu Boddeti OOD 102 45 0 21 Dec 2022
In and Out-of-Domain Text Adversarial Robustness via Label Smoothing Yahan Yang Soham Dan Dan Roth Insup Lee 80 5 0 20 Dec 2022
A Comprehensive Study of the Robustness for LiDAR-based 3D Object Detectors against Adversarial Attacks Yifan Zhang Xianqiang Lyu Yixuan Yuan AAML 3DPC 75 34 0 20 Dec 2022
TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization Bairu Hou Jinghan Jia Yihua Zhang Guanhua Zhang Yang Zhang Sijia Liu Shiyu Chang SILM AAML 66 24 0 19 Dec 2022
Minimizing Maximum Model Discrepancy for Transferable Black-box Targeted Attacks Anqi Zhao Tong Chu Yahao Liu Wen Li Jingjing Li Lixin Duan AAML 74 18 0 18 Dec 2022
Confidence-aware Training of Smoothed Classifiers for Certified Robustness Jongheon Jeong Seojin Kim Jinwoo Shin AAML 99 7 0 18 Dec 2022
Robust Explanation Constraints for Neural Networks Matthew Wicker Juyeon Heo Luca Costabello Adrian Weller FAtt 65 18 0 16 Dec 2022
Adversarial Example Defense via Perturbation Grading Strategy Shaowei Zhu Wanli Lyu Bin Li Z. Yin Bin Luo AAML 78 1 0 16 Dec 2022
Alternating Objectives Generates Stronger PGD-Based Adversarial Attacks Nikolaos Antoniou Efthymios Georgiou Alexandros Potamianos AAML 71 5 0 15 Dec 2022
Understanding Zero-Shot Adversarial Robustness for Large-Scale Models Chengzhi Mao Scott Geng Junfeng Yang Xin Eric Wang Carl Vondrick VLM 102 71 0 14 Dec 2022
SAIF: Sparse Adversarial and Imperceptible Attack Framework Tooba Imtiaz Morgan Kohler Jared Miller Zifeng Wang Octavia Camps Mario Sznaier Octavia Camps Jennifer Dy AAML 100 0 0 14 Dec 2022
Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial Detection P. Lorenz Margret Keuper J. Keuper AAML 97 7 0 13 Dec 2022
Adversarially Robust Video Perception by Seeing Motion Lingyu Zhang Chengzhi Mao Junfeng Yang Carl Vondrick VGen AAML 95 2 0 13 Dec 2022
Robust Perception through Equivariance Chengzhi Mao Lingyu Zhang Abhishek Joshi Junfeng Yang Hongya Wang Carl Vondrick BDL AAML 98 8 0 12 Dec 2022
REAP: A Large-Scale Realistic Adversarial Patch Benchmark Nabeel Hingun Chawin Sitawarin Jerry Li David Wagner AAML 97 15 0 12 Dec 2022
DISCO: Adversarial Defense with Local Implicit Functions Chih-Hui Ho Nuno Vasconcelos AAML 130 39 0 11 Dec 2022
General Adversarial Defense Against Black-box Attacks via Pixel Level and Feature Level Distribution Alignments Xiaogang Xu Hengshuang Zhao Philip Torr Jiaya Jia AAML 61 2 0 11 Dec 2022
Mitigating Adversarial Gray-Box Attacks Against Phishing Detectors Giovanni Apruzzese V. S. Subrahmanian AAML 87 21 0 11 Dec 2022
Targeted Adversarial Attacks on Deep Reinforcement Learning Policies via Model Checking Dennis Gross T. D. Simão N. Jansen G. Pérez AAML 95 2 0 10 Dec 2022
QVIP: An ILP-based Formal Verification Approach for Quantized Neural Networks Yedi Zhang Zhe Zhao Fu Song Hao Fei Tao Chen Jun Sun 69 18 0 10 Dec 2022
Fairify: Fairness Verification of Neural Networks Sumon Biswas Hridesh Rajan 81 26 0 08 Dec 2022
Leveraging Unlabeled Data to Track Memorization Mahsa Forouzesh Hanie Sedghi Patrick Thiran NoLa TDI 87 4 0 08 Dec 2022
PKDGA: A Partial Knowledge-based Domain Generation Algorithm for Botnets Lihai Nie Xiaoyang Shan Laiping Zhao Keqiu Li 66 5 0 08 Dec 2022
Pre-trained Encoders in Self-Supervised Learning Improve Secure and Privacy-preserving Supervised Learning Hongbin Liu Wenjie Qu Jinyuan Jia Neil Zhenqiang Gong SSL 71 6 0 06 Dec 2022
QEBVerif: Quantization Error Bound Verification of Neural Networks Yedi Zhang Fu Song Jun Sun MQ 99 12 0 06 Dec 2022
$Multiple Perturbation Attack: Attack Pixelwise Under Different $\ell_p$-norms For Better Adversarial Performance$ Multiple Perturbation Attack: Attack Pixelwise Under Different $\ell_p$ -norms For Better Adversarial Performance Ngoc N. Tran Anh Tuan Bui Dinh Q. Phung Trung Le AAML 70 1 0 05 Dec 2022
FaceQAN: Face Image Quality Assessment Through Adversarial Noise Exploration Žiga Babnik Peter Peer Vitomir Štruc CVBM AAML 73 19 0 05 Dec 2022
Bayesian Learning with Information Gain Provably Bounds Risk for a Robust Adversarial Defense Bao Gia Doan Ehsan Abbasnejad Javen Qinfeng Shi Damith Ranashinghe AAML OOD 89 8 0 05 Dec 2022
Refiner: Data Refining against Gradient Leakage Attacks in Federated Learning Mingyuan Fan Cen Chen Chengyu Wang Ximeng Liu Wenmeng Zhou AAML FedML 118 0 0 05 Dec 2022
Analogical Math Word Problems Solving with Enhanced Problem-Solution Association Zhenwen Liang Jipeng Zhang Xiangliang Zhang AIMat 69 17 0 01 Dec 2022
Hijack Vertical Federated Learning Models As One Party Pengyu Qiu Xuhong Zhang Shouling Ji Changjiang Li Yuwen Pu Xing Yang Ting Wang FedML 124 6 0 01 Dec 2022
Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations Hong-Ming Chiu Richard Y. Zhang AAML 88 3 0 30 Nov 2022
AdvMask: A Sparse Adversarial Attack Based Data Augmentation Method for Image Classification Suorong Yang Jinqiao Li Jian Zhao S. Furao AAML 69 6 0 29 Nov 2022
Backdoor Vulnerabilities in Normally Trained Deep Learning Models Guanhong Tao Zhenting Wang Shuyang Cheng Shiqing Ma Shengwei An Yingqi Liu Guangyu Shen Zhuo Zhang Yunshu Mao Xiangyu Zhang SILM 75 17 0 29 Nov 2022
Interpretations Cannot Be Trusted: Stealthy and Effective Adversarial Perturbations against Interpretable Deep Learning Eldor Abdukhamidov Mohammed Abuhamad Simon S. Woo Eric Chan-Tin Tamer Abuhmed AAML 68 9 0 29 Nov 2022
Data Poisoning Attack Aiming the Vulnerability of Continual Learning Gyojin Han Jaehyun Choi H. Hong Junmo Kim AAML 35 2 0 29 Nov 2022
Adversarial Artifact Detection in EEG-Based Brain-Computer Interfaces Xiaoqing Chen Dongrui Wu AAML 93 4 0 28 Nov 2022
Rethinking the Number of Shots in Robust Model-Agnostic Meta-Learning Xiaoyue Duan Guoliang Kang Runqi Wang Shumin Han Shenjun Xue Tian Wang Baochang Zhang 83 2 0 28 Nov 2022
Imperceptible Adversarial Attack via Invertible Neural Networks Zihan Chen Zifan Wang Junjie Huang Wentao Zhao Xiao Liu Dejian Guan AAML 135 22 0 28 Nov 2022
Adversarial Rademacher Complexity of Deep Neural Networks Jiancong Xiao Yanbo Fan Ruoyu Sun Zhimin Luo AAML 64 23 0 27 Nov 2022
Foiling Explanations in Deep Neural Networks Snir Vitrack Tamam Raz Lapid Moshe Sipper AAML 75 17 0 27 Nov 2022