Papers citing 'Towards Deep Learning Models Resistant to Adversarial Attacks'

Title
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional NetworksNeural Information Processing Systems (NeurIPS), 2019 Qiyang Li Saminul Haque Cem Anil James Lucas Roger C. Grosse Joern-Henrik Jacobsen 333 119 0 03 Nov 2019
Who is Real Bob? Adversarial Attacks on Speaker Recognition SystemsIEEE Symposium on Security and Privacy (IEEE S&P), 2019 Guangke Chen Sen Chen Lingling Fan Xiaoning Du Zhe Zhao Fu Song Yang Liu AAML 234 225 0 03 Nov 2019
Online Robustness Training for Deep Reinforcement Learning Marc Fischer M. Mirman Steven Stalder Martin Vechev OnRL 306 49 0 03 Nov 2019
MadNet: Using a MAD Optimization for Defending Against Adversarial Attacks Shai Rozenberg G. Elidan Ran El-Yaniv AAML 104 1 0 03 Nov 2019
Adversarial Music: Real World Audio Adversary Against Wake-word Detection SystemNeural Information Processing Systems (NeurIPS), 2019 Juncheng Billy Li Shuhui Qu Xinjian Li Joseph Szurley J. Zico Kolter Florian Metze AAML 307 71 0 31 Oct 2019
Making an Invisibility Cloak: Real World Adversarial Attacks on Object DetectorsEuropean Conference on Computer Vision (ECCV), 2019 Zuxuan Wu Ser-Nam Lim L. Davis Tom Goldstein AAML 323 302 0 31 Oct 2019
Enhancing Certifiable Robustness via a Deep Model Ensemble Huan Zhang Minhao Cheng Cho-Jui Hsieh 126 9 0 31 Oct 2019
A Decentralized Proximal Point-type Method for Saddle Point Problems Weijie Liu Aryan Mokhtari Asuman Ozdaglar S. Pattathil Zebang Shen Nenggan Zheng 281 33 0 31 Oct 2019
Investigating Resistance of Deep Learning-based IDS against Adversaries using min-max Optimization Rana Abou-Khamis Omair Shafiq Ashraf Matrawy AAML 166 48 0 30 Oct 2019
Fault Tolerance of Neural Networks in Adversarial SettingsJournal of Intelligent & Fuzzy Systems (JIFS), 2019 Vasisht Duddu N. Pillai D. V. Rao V. Balas SILM AAML 186 12 0 30 Oct 2019
Efficiently avoiding saddle points with zero order methods: No gradients requiredNeural Information Processing Systems (NeurIPS), 2019 Lampros Flokas Emmanouil-Vasileios Vlatakis-Gkaragkounis Georgios Piliouras 146 35 0 29 Oct 2019
Certified Adversarial Robustness for Deep Reinforcement LearningConference on Robot Learning (CoRL), 2019 Björn Lütjens Michael Everett Jonathan P. How AAML 182 102 0 28 Oct 2019
Dr.VOT : Measuring Positive and Negative Voice Onset Time in the WildInterspeech (Interspeech), 2019 Yosi Shrem Matthew A. Goldrick Joseph Keshet 62 13 0 27 Oct 2019
Adversarial Defense via Local Flatness RegularizationInternational Conference on Information Photonics (ICIP), 2019 Jia Xu Yiming Li Yong Jiang Shutao Xia AAML 244 21 0 27 Oct 2019
Understanding and Quantifying Adversarial Examples Existence in Linear ClassificationInternational Conference on Machine Learning and Computing (ICMLC), 2019 Xupeng Shi A. Ding AAML 85 3 0 27 Oct 2019
Effectiveness of random deep feature selection for securing image manipulation detectors against adversarial examplesIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019 Mauro Barni Ehsan Nowroozi B. Tondi Bowen Zhang AAML 182 17 0 25 Oct 2019
A Simple Dynamic Learning Rate Tuning Algorithm For Automated Training of DNNs Koyel Mukherjee Alind Khare Ashish Verma 143 20 0 25 Oct 2019
Label Smoothing and Logit Squeezing: A Replacement for Adversarial Training? Ali Shafahi Amin Ghiasi Furong Huang Tom Goldstein AAML 128 42 0 25 Oct 2019
ATZSL: Defensive Zero-Shot Recognition in the Presence of AdversariesIEEE transactions on multimedia (IEEE TMM), 2019 Xingxing Zhang Shupeng Gui Zhenfeng Zhu Yao Zhao Ji Liu VLM 129 10 0 24 Oct 2019
Diametrical Risk Minimization: Theory and ComputationsMachine-mediated learning (ML), 2019 Matthew Norton Pratiksha Agrawal 257 20 0 24 Oct 2019
Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial AttacksInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Alexander Levine Soheil Feizi AAML 117 63 0 23 Oct 2019
A Useful Taxonomy for Adversarial Robustness of Neural NetworksTrends in Computer Science and Information Technology (TCSIT), 2019 L. Smith AAML 130 6 0 23 Oct 2019
Structure Matters: Towards Generating Transferable Adversarial ImagesEuropean Conference on Artificial Intelligence (ECAI), 2019 Dan Peng Zizhan Zheng Linhao Luo Xiaofeng Zhang AAML 194 2 0 22 Oct 2019
An Alternative Surrogate Loss for PGD-based Adversarial Testing Sven Gowal J. Uesato Chongli Qin Po-Sen Huang Timothy A. Mann Pushmeet Kohli AAML 268 90 0 21 Oct 2019
Improving Sequence Modeling Ability of Recurrent Neural Networks via Sememes Yujia Qin Fanchao Qi Sicong Ouyang Zhiyuan Liu Cheng Yang Yasheng Wang Qun Liu Maosong Sun 164 5 0 20 Oct 2019
Adversarial Attacks on Spoofing Countermeasures of automatic speaker verificationAutomatic Speech Recognition & Understanding (ASRU), 2019 Songxiang Liu Haibin Wu Hung-yi Lee Helen Meng AAML 134 68 0 19 Oct 2019
Are Perceptually-Aligned Gradients a General Property of Robust Classifiers? Simran Kaur Jeremy M. Cohen Zachary Chase Lipton OOD AAML 216 68 0 18 Oct 2019
A Fast Saddle-Point Dynamical System Approach to Robust Deep Learning Yasaman Esfandiari Aditya Balu K. Ebrahimi Umesh Vaidya N. Elia Soumik Sarkar OOD 169 3 0 18 Oct 2019
Enforcing Linearity in DNN succours Robustness and Adversarial Image GenerationInternational Conference on Artificial Neural Networks (ICANN), 2019 A. Sarkar Nikhil Kumar Gupta Raghu Sesha Iyengar AAML 125 11 0 17 Oct 2019
Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets Yogesh Balaji Tom Goldstein Judy Hoffman AAML 295 111 0 17 Oct 2019
A New Defense Against Adversarial Images: Turning a Weakness into a StrengthNeural Information Processing Systems (NeurIPS), 2019 Tao Yu Shengyuan Hu Chuan Guo Wei-Lun Chao Kilian Q. Weinberger AAML 206 111 0 16 Oct 2019
MUTE: Data-Similarity Driven Multi-hot Target Encoding for Neural Network Design Mayoore S. Jaiswal Bumboo Kang Jinho Lee Minsik Cho 101 2 0 15 Oct 2019
Extracting robust and accurate features via a robust information bottleneckIEEE Journal on Selected Areas in Information Theory (JSAIT), 2019 Ankit Pensia Varun Jog Po-Ling Loh AAML 134 23 0 15 Oct 2019
ODE guided Neural Data Augmentation Techniques for Time Series Data and its Benefits on Robustness A. Sarkar A. Raj Raghu Sesha Iyengar AAML AI4TS 195 0 0 15 Oct 2019
Understanding Misclassifications by Attributes Sadaf Gulshad Zeynep Akata J. H. Metzen A. Smeulders AAML 145 0 0 15 Oct 2019
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box OptimizationNeural Information Processing Systems (NeurIPS), 2019 Xiangyi Chen Sijia Liu Kaidi Xu Xingguo Li Xue Lin Mingyi Hong David Cox ODL 180 130 0 15 Oct 2019
DeepSearch: A Simple and Effective Blackbox Attack for Deep Neural Networks Fuyuan Zhang Sankalan Pal Chowdhury M. Christakis AAML 150 8 0 14 Oct 2019
Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks David Stutz Matthias Hein Bernt Schiele AAML 293 5 0 14 Oct 2019
Man-in-the-Middle Attacks against Machine Learning Classifiers via Malicious Generative ModelsIEEE Transactions on Dependable and Secure Computing (TDSC), 2019 Derui Wang Wang Chaoran Li S. Wen Surya Nepal Yang Xiang AAML 109 40 0 14 Oct 2019
On Robustness of Neural Ordinary Differential EquationsInternational Conference on Learning Representations (ICLR), 2019 Hanshu Yan Jiawei Du Vincent Y. F. Tan Jiashi Feng OOD 321 154 0 12 Oct 2019
Hear "No Evil", See "Kenansville": Efficient and Transferable Black-Box Attacks on Speech Recognition and Voice Identification Systems H. Abdullah Muhammad Sajidur Rahman Washington Garcia Logan Blue Kevin Warren Anurag Swarnim Yadav T. Shrimpton Patrick Traynor AAML 133 95 0 11 Oct 2019
Noise as a Resource for Learning in Knowledge Distillation Elahe Arani F. Sarfraz Bahram Zonooz 168 6 0 11 Oct 2019
Verification of Neural Networks: Specifying Global Robustness using Generative Models Nathanaël Fijalkow M. Gupta AAML 57 3 0 11 Oct 2019
Information Aware Max-Norm Dirichlet Networks for Predictive Uncertainty Estimation Theodoros Tsiligkaridis UQCV BDL 203 9 0 10 Oct 2019
Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer MarginInternational Conference on Learning Representations (ICLR), 2019 Colin Wei Tengyu Ma AAML OOD 482 88 0 09 Oct 2019
Deep Latent Defence Giulio Zizzo C. Hankin S. Maffeis K. Jones AAML 145 2 0 09 Oct 2019
Adversarial Learning of Deepfakes in Accounting Marco Schreyer Timur Sattarov Bernd Reimer Damian Borth AAML 151 26 0 09 Oct 2019
SmoothFool: An Efficient Framework for Computing Smooth Adversarial PerturbationsIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2019 Ali Dabouei Sobhan Soleymani Fariborz Taherkhani J. Dawson Nasser M. Nasrabadi AAML 233 22 0 08 Oct 2019
Directional Adversarial Training for Cost Sensitive Deep Learning Classification ApplicationsEngineering applications of artificial intelligence (EAAI), 2019 M. Terzi Gian Antonio Susto Pratik Chaudhari OOD AAML 126 17 0 08 Oct 2019
AdvSPADE: Realistic Unrestricted Attacks for Semantic Segmentation Guangyu Shen Chengzhi Mao Junfeng Yang Baishakhi Ray GAN 174 14 0 06 Oct 2019