Towards Deep Learning Models Resistant to Adversarial Attacks

19 June 2017

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

50 / 6,519 papers shown

Title
Enforcing Linearity in DNN succours Robustness and Adversarial Image Generation A. Sarkar Nikhil Kumar Gupta Raghu Sesha Iyengar AAML 16 11 0 17 Oct 2019
Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets Yogesh Balaji Tom Goldstein Judy Hoffman AAML 134 103 0 17 Oct 2019
A New Defense Against Adversarial Images: Turning a Weakness into a Strength Tao Yu Shengyuan Hu Chuan Guo Wei-Lun Chao Kilian Q. Weinberger AAML 58 101 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 21 2 0 15 Oct 2019
Extracting robust and accurate features via a robust information bottleneck Ankit Pensia Varun Jog Po-Ling Loh AAML 26 20 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 34 0 0 15 Oct 2019
Understanding Misclassifications by Attributes Sadaf Gulshad Zeynep Akata J. H. Metzen A. Smeulders AAML 38 0 0 15 Oct 2019
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization Xiangyi Chen Sijia Liu Kaidi Xu Xingguo Li Xue Lin Mingyi Hong David Cox ODL 19 105 0 15 Oct 2019
DeepSearch: A Simple and Effective Blackbox Attack for Deep Neural Networks Fuyuan Zhang Sankalan Pal Chowdhury M. Christakis AAML 28 8 0 14 Oct 2019
Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks David Stutz Matthias Hein Bernt Schiele AAML 25 5 0 14 Oct 2019
Man-in-the-Middle Attacks against Machine Learning Classifiers via Malicious Generative Models Derui Wang Wang Chaoran Li S. Wen Surya Nepal Yang Xiang AAML 13 32 0 14 Oct 2019
On Robustness of Neural Ordinary Differential Equations Hanshu Yan Jiawei Du Vincent Y. F. Tan Jiashi Feng OOD 27 138 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 33 87 0 11 Oct 2019
Noise as a Resource for Learning in Knowledge Distillation Elahe Arani F. Sarfraz Bahram Zonooz 18 6 0 11 Oct 2019
Verification of Neural Networks: Specifying Global Robustness using Generative Models Nathanaël Fijalkow M. Gupta AAML 22 2 0 11 Oct 2019
Information Aware Max-Norm Dirichlet Networks for Predictive Uncertainty Estimation Theodoros Tsiligkaridis UQCV BDL 16 8 0 10 Oct 2019
Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin Colin Wei Tengyu Ma AAML OOD 38 85 0 09 Oct 2019
Deep Latent Defence Giulio Zizzo C. Hankin S. Maffeis K. Jones AAML 38 2 0 09 Oct 2019
Adversarial Learning of Deepfakes in Accounting Marco Schreyer Timur Sattarov Bernd Reimer Damian Borth AAML 30 26 0 09 Oct 2019
SmoothFool: An Efficient Framework for Computing Smooth Adversarial Perturbations Ali Dabouei Sobhan Soleymani Fariborz Taherkhani J. Dawson Nasser M. Nasrabadi AAML 104 19 0 08 Oct 2019
Directional Adversarial Training for Cost Sensitive Deep Learning Classification Applications M. Terzi Gian Antonio Susto Pratik Chaudhari OOD AAML 16 15 0 08 Oct 2019
AdvSPADE: Realistic Unrestricted Attacks for Semantic Segmentation Guangyu Shen Chengzhi Mao Junfeng Yang Baishakhi Ray GAN 28 12 0 06 Oct 2019
Yet another but more efficient black-box adversarial attack: tiling and evolution strategies Laurent Meunier Cen Chen Li Wang MLAU AAML 33 40 0 05 Oct 2019
Adversarial Examples for Cost-Sensitive Classifiers Mahdi Akbari Zarkesh A. Lohn Ali Movaghar SILM AAML 24 3 0 04 Oct 2019
On the Detection of Digital Face Manipulation H. Dang Anand Balakrishnan J. Stehouwer Connor Christopherson David Wingate CVBM AAML 30 534 0 03 Oct 2019
Information based Deep Clustering: An experimental study Jizong Peng Christian Desrosiers M. Pedersoli 27 1 0 03 Oct 2019
Verification of Neural Network Behaviour: Formal Guarantees for Power System Applications Andreas Venzke Spyros Chatzivasileiadis 14 67 0 03 Oct 2019
Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions He Zhao Trung Le Paul Montague O. Vel Tamas Abraham Dinh Q. Phung AAML 28 8 0 03 Oct 2019
Adversarially Robust Few-Shot Learning: A Meta-Learning Approach Micah Goldblum Liam H. Fowl Tom Goldstein 22 13 0 02 Oct 2019
Analyzing and Improving Neural Networks by Generating Semantic Counterexamples through Differentiable Rendering Lakshya Jain Varun Chandrasekaran Uyeong Jang Wilson Wu Andrew Lee Andy Yan Steven Chen S. Jha S. Seshia AAML 21 11 0 02 Oct 2019
An Efficient and Margin-Approaching Zero-Confidence Adversarial Attack Yang Zhang Shiyu Chang Mo Yu Kaizhi Qian AAML 23 2 0 01 Oct 2019
Truth or Backpropaganda? An Empirical Investigation of Deep Learning Theory Micah Goldblum Jonas Geiping Avi Schwarzschild Michael Moeller Tom Goldstein 21 32 0 01 Oct 2019
Predicting with High Correlation Features Devansh Arpit Caiming Xiong R. Socher OODD OOD 22 7 0 01 Oct 2019
Role of Spatial Context in Adversarial Robustness for Object Detection Aniruddha Saha Akshayvarun Subramanya Koninika Patil Hamed Pirsiavash ObjD AAML 32 53 0 30 Sep 2019
Synthesizing Action Sequences for Modifying Model Decisions Goutham Ramakrishnan Yun Chan Lee Aws Albarghouthi 20 32 0 30 Sep 2019
Hidden Trigger Backdoor Attacks Aniruddha Saha Akshayvarun Subramanya Hamed Pirsiavash 36 613 0 30 Sep 2019
Black-box Adversarial Attacks with Bayesian Optimization Satya Narayan Shukla Anit Kumar Sahu Devin Willmott J. Zico Kolter AAML MLAU 14 30 0 30 Sep 2019
Min-Max Optimization without Gradients: Convergence and Applications to Adversarial ML Sijia Liu Songtao Lu Xiangyi Chen Yao Feng Kaidi Xu Abdullah Al-Dujaili Mingyi Hong Una-May Obelilly 38 26 0 30 Sep 2019
Deep k-NN Defense against Clean-label Data Poisoning Attacks Neehar Peri Neal Gupta Wenjie Huang Liam H. Fowl Chen Zhu S. Feizi Tom Goldstein John P. Dickerson AAML 19 6 0 29 Sep 2019
Library network, a possible path to explainable neural networks J. H. Lee AAML AI4CE 11 0 0 29 Sep 2019
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts Yu Sun Xiaolong Wang Zhuang Liu John Miller Alexei A. Efros Moritz Hardt TTA OOD 27 92 0 29 Sep 2019
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 29 18 0 27 Sep 2019
Lower Bounds on Adversarial Robustness from Optimal Transport A. Bhagoji Daniel Cullina Prateek Mittal OOD OT AAML 32 92 0 26 Sep 2019
Towards neural networks that provably know when they don't know Alexander Meinke Matthias Hein OODD 33 139 0 26 Sep 2019
Towards Explainable Artificial Intelligence Wojciech Samek K. Müller XAI 32 437 0 26 Sep 2019
FreeLB: Enhanced Adversarial Training for Natural Language Understanding Chen Zhu Yu Cheng Zhe Gan S. Sun Tom Goldstein Jingjing Liu AAML 234 438 0 25 Sep 2019
Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks Tianyu Pang Kun Xu Jun Zhu AAML 28 103 0 25 Sep 2019
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack Minhao Cheng Simranjit Singh Patrick H. Chen Pin-Yu Chen Sijia Liu Cho-Jui Hsieh AAML 134 219 0 24 Sep 2019
MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples Jinyuan Jia Ahmed Salem Michael Backes Yang Zhang Neil Zhenqiang Gong 33 384 0 23 Sep 2019
FENCE: Feasible Evasion Attacks on Neural Networks in Constrained Environments Alesia Chernikova Alina Oprea AAML 19 35 0 23 Sep 2019