Towards Deep Neural Network Architectures Robust to Adversarial Examples

11 December 2014

Papers citing "Towards Deep Neural Network Architectures Robust to Adversarial Examples"

50 / 158 papers shown

Title
The Vulnerability of the Neural Networks Against Adversarial Examples in Deep Learning Algorithms Rui Zhao AAML 34 1 0 02 Nov 2020
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable? Anna-Kathrin Kopetzki Bertrand Charpentier Daniel Zügner Sandhya Giri Stephan Günnemann 23 45 0 28 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
Defending Adversarial Examples via DNN Bottleneck Reinforcement Wenqing Liu Miaojing Shi Teddy Furon Li Li AAML 26 8 0 12 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 27 73 0 07 Aug 2020
Robustifying Reinforcement Learning Agents via Action Space Adversarial Training Kai Liang Tan Yasaman Esfandiari Xian Yeow Lee Aakanksha S. Sarkar AAML 26 55 0 14 Jul 2020
Adversarial Attacks against Neural Networks in Audio Domain: Exploiting Principal Components Ken Alparslan Yigit Can Alparslan Matthew Burlick AAML 24 8 0 14 Jul 2020
Deep Learning Defenses Against Adversarial Examples for Dynamic Risk Assessment Xabier Echeberria-Barrio Amaia Gil-Lerchundi Ines Goicoechea-Telleria Raul Orduna Urrutia AAML 19 5 0 02 Jul 2020
ConFoc: Content-Focus Protection Against Trojan Attacks on Neural Networks Miguel Villarreal-Vasquez B. Bhargava AAML 17 38 0 01 Jul 2020
Counterexample-Guided Learning of Monotonic Neural Networks Aishwarya Sivaraman G. Farnadi T. Millstein Mathias Niepert 24 50 0 16 Jun 2020
Defensive Approximation: Securing CNNs using Approximate Computing Amira Guesmi Ihsen Alouani Khaled N. Khasawneh M. Baklouti T. Frikha Mohamed Abid Nael B. Abu-Ghazaleh AAML 19 37 0 13 Jun 2020
Towards Robust Pattern Recognition: A Review Xu-Yao Zhang Cheng-Lin Liu C. Suen OOD HAI 19 103 0 12 Jun 2020
Calibrated Surrogate Losses for Adversarially Robust Classification Han Bao Clayton Scott Masashi Sugiyama 29 45 0 28 May 2020
Stable and expressive recurrent vision models Drew Linsley A. Ashok L. Govindarajan Rex G Liu Thomas Serre 19 45 0 22 May 2020
Toward Adversarial Robustness via Semi-supervised Robust Training Yiming Li Baoyuan Wu Yan Feng Yanbo Fan Yong Jiang Zhifeng Li Shutao Xia AAML 87 13 0 16 Mar 2020
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness Ahmadreza Jeddi M. Shafiee Michelle Karg C. Scharfenberger A. Wong OOD AAML 67 63 0 02 Mar 2020
Gödel's Sentence Is An Adversarial Example But Unsolvable Xiaodong Qi Lansheng Han AAML 27 0 0 25 Feb 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
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models Lin Chen Yifei Min Mingrui Zhang Amin Karbasi OOD 38 64 0 11 Feb 2020
Understanding the Decision Boundary of Deep Neural Networks: An Empirical Study David Mickisch F. Assion Florens Greßner W. Günther M. Motta AAML 19 34 0 05 Feb 2020
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 18 104 0 13 Nov 2019
HAWKEYE: Adversarial Example Detector for Deep Neural Networks Jinkyu Koo Michael A. Roth S. Bagchi AAML 106 3 0 22 Sep 2019
Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks Ka-Ho Chow Wenqi Wei Yanzhao Wu Ling Liu AAML 22 15 0 21 Aug 2019
Once a MAN: Towards Multi-Target Attack via Learning Multi-Target Adversarial Network Once Jiangfan Han Xiaoyi Dong Ruimao Zhang Dongdong Chen Weiming Zhang Nenghai Yu Ping Luo Xiaogang Wang AAML 24 28 0 14 Aug 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack Francesco Croce Matthias Hein AAML 43 474 0 03 Jul 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
Enhancing Gradient-based Attacks with Symbolic Intervals Shiqi Wang Yizheng Chen Ahmed Abdou Suman Jana AAML 28 15 0 05 Jun 2019
Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward A. Qayyum Muhammad Usama Junaid Qadir Ala I. Al-Fuqaha AAML 21 187 0 29 May 2019
Biometric Backdoors: A Poisoning Attack Against Unsupervised Template Updating Giulio Lovisotto Simon Eberz Ivan Martinovic AAML 21 35 0 22 May 2019
Testing DNN Image Classifiers for Confusion & Bias Errors Yuchi Tian Ziyuan Zhong Vicente Ordonez Gail E. Kaiser Baishakhi Ray 24 52 0 20 May 2019
Defending against Whitebox Adversarial Attacks via Randomized Discretization Yuchen Zhang Percy Liang AAML 32 75 0 25 Mar 2019
Scalable Differential Privacy with Certified Robustness in Adversarial Learning Nhathai Phan My T. Thai Han Hu R. Jin Tong Sun Dejing Dou 27 14 0 23 Mar 2019
Detecting Overfitting via Adversarial Examples Roman Werpachowski András Gyorgy Csaba Szepesvári TDI 26 45 0 06 Mar 2019
Accelerating Training of Deep Neural Networks with a Standardization Loss Jasmine Collins Johannes Ballé Jonathon Shlens 21 3 0 03 Mar 2019
Adversarial Attack and Defense on Point Sets Jiancheng Yang Qiang Zhang Rongyao Fang Bingbing Ni Jinxian Liu Qi Tian 3DPC 24 122 0 28 Feb 2019
Daedalus: Breaking Non-Maximum Suppression in Object Detection via Adversarial Examples Derui Wang Chaoran Li S. Wen Qing-Long Han Surya Nepal Xiangyu Zhang Yang Xiang AAML 30 40 0 06 Feb 2019
Optimization Problems for Machine Learning: A Survey Claudio Gambella Bissan Ghaddar Joe Naoum-Sawaya AI4CE 30 178 0 16 Jan 2019
Defense-VAE: A Fast and Accurate Defense against Adversarial Attacks Xiang Li Shihao Ji AAML 27 26 0 17 Dec 2018
Combatting Adversarial Attacks through Denoising and Dimensionality Reduction: A Cascaded Autoencoder Approach R. Sahay Rehana Mahfuz Aly El Gamal 17 33 0 07 Dec 2018
Adversarial Defense of Image Classification Using a Variational Auto-Encoder Yi-Si Luo H. Pfister AAML 11 9 0 07 Dec 2018
Regularized Ensembles and Transferability in Adversarial Learning Yifan Chen Yevgeniy Vorobeychik AAML 13 2 0 05 Dec 2018
Robustness via curvature regularization, and vice versa Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi J. Uesato P. Frossard AAML 29 318 0 23 Nov 2018
Theoretical Analysis of Adversarial Learning: A Minimax Approach Zhuozhuo Tu Jingwei Zhang Dacheng Tao AAML 15 68 0 13 Nov 2018
MixTrain: Scalable Training of Verifiably Robust Neural Networks Yue Zhang Yizheng Chen Ahmed Abdou Mohsen Guizani AAML 21 23 0 06 Nov 2018
Provable Robustness of ReLU networks via Maximization of Linear Regions Francesco Croce Maksym Andriushchenko Matthias Hein 26 166 0 17 Oct 2018
Physics-Driven Regularization of Deep Neural Networks for Enhanced Engineering Design and Analysis M. A. Nabian Hadi Meidani PINN AI4CE 21 57 0 11 Oct 2018
Fast Geometrically-Perturbed Adversarial Faces Ali Dabouei Sobhan Soleymani J. Dawson Nasser M. Nasrabadi CVBM AAML 29 65 0 24 Sep 2018
HashTran-DNN: A Framework for Enhancing Robustness of Deep Neural Networks against Adversarial Malware Samples Deqiang Li Ramesh Baral Tao Li Han Wang Qianmu Li Shouhuai Xu AAML 25 21 0 18 Sep 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