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Towards Evaluating the Robustness of Neural Networks

16 August 2016

Papers citing "Towards Evaluating the Robustness of Neural Networks"

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Title
Defending against Whitebox Adversarial Attacks via Randomized Discretization Yuchen Zhang Percy Liang AAML 84 76 0 25 Mar 2019
The LogBarrier adversarial attack: making effective use of decision boundary information Chris Finlay Aram-Alexandre Pooladian Adam M. Oberman AAML 79 25 0 25 Mar 2019
Robust Neural Networks using Randomized Adversarial Training Alexandre Araujo Laurent Meunier Rafael Pinot Benjamin Négrevergne AAML OOD 48 36 0 25 Mar 2019
A Formalization of Robustness for Deep Neural Networks T. Dreossi Shromona Ghosh Alberto L. Sangiovanni-Vincentelli Sanjit A. Seshia GAN 76 30 0 24 Mar 2019
Variational Inference with Latent Space Quantization for Adversarial Resilience Vinay Kyatham P. PrathoshA. Tarun Kumar Yadav Deepak Mishra Dheeraj Mundhra AAML 48 3 0 24 Mar 2019
Improving Adversarial Robustness via Guided Complement Entropy Hao-Yun Chen Jhao-Hong Liang Shih-Chieh Chang Jia Pan Yu-Ting Chen Wei Wei Da-Cheng Juan AAML 67 49 0 23 Mar 2019
Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition Yao Qin Nicholas Carlini Ian Goodfellow G. Cottrell Colin Raffel AAML 113 381 0 22 Mar 2019
Adversarial camera stickers: A physical camera-based attack on deep learning systems Juncheng Billy Li Frank R. Schmidt J. Zico Kolter AAML 85 170 0 21 Mar 2019
Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes Matt Jordan Justin Lewis A. Dimakis AAML 79 57 0 20 Mar 2019
On the Robustness of Deep K-Nearest Neighbors Chawin Sitawarin David Wagner AAML OOD 140 58 0 20 Mar 2019
Practical Hidden Voice Attacks against Speech and Speaker Recognition Systems H. Abdullah Washington Garcia Christian Peeters Patrick Traynor Kevin R. B. Butler Joseph N. Wilson AAML 72 168 0 18 Mar 2019
On Certifying Non-uniform Bound against Adversarial Attacks Chen Liu Ryota Tomioka Volkan Cevher AAML 81 19 0 15 Mar 2019
Attribution-driven Causal Analysis for Detection of Adversarial Examples Susmit Jha Sunny Raj S. Fernandes Sumit Kumar Jha S. Jha Gunjan Verma B. Jalaeian A. Swami AAML 75 17 0 14 Mar 2019
Smart Home Personal Assistants: A Security and Privacy Review Jide S. Edu Jose Such Guillermo Suarez-Tangil 41 95 0 13 Mar 2019
Neural Network Model Extraction Attacks in Edge Devices by Hearing Architectural Hints Xing Hu Ling Liang Lei Deng Shuangchen Li Xinfeng Xie Yu Ji Yufei Ding Chang Liu T. Sherwood Yuan Xie AAML MLAU 68 36 0 10 Mar 2019
Semantics Preserving Adversarial Learning Ousmane Amadou Dia Elnaz Barshan Reza Babanezhad AAML GAN 113 2 0 10 Mar 2019
A Learnable ScatterNet: Locally Invariant Convolutional Layers Fergal Cotter N. Kingsbury 57 22 0 07 Mar 2019
Attack Type Agnostic Perceptual Enhancement of Adversarial Images Bilgin Aksoy A. Temi̇zel AAML 44 5 0 07 Mar 2019
Detecting Overfitting via Adversarial Examples Roman Werpachowski András Gyorgy Csaba Szepesvári TDI 86 45 0 06 Mar 2019
Statistical Guarantees for the Robustness of Bayesian Neural Networks L. Cardelli Marta Kwiatkowska Luca Laurenti Nicola Paoletti A. Patané Matthew Wicker AAML 89 54 0 05 Mar 2019
Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search Abhimanyu Dubey Laurens van der Maaten Zeki Yalniz Yixuan Li D. Mahajan AAML 115 66 0 05 Mar 2019
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations Saeid Asgari Taghanaki Kumar Abhishek Shekoofeh Azizi Ghassan Hamarneh AAML 89 41 0 03 Mar 2019
PuVAE: A Variational Autoencoder to Purify Adversarial Examples Uiwon Hwang Jaewoo Park Hyemi Jang Sungroh Yoon N. Cho AAML 75 77 0 02 Mar 2019
On the Effectiveness of Low Frequency Perturbations Yash Sharma G. Ding Marcus A. Brubaker AAML 96 126 0 28 Feb 2019
Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN Ke Sun Zhanxing Zhu Zhouchen Lin AAML 62 20 0 28 Feb 2019
Adversarial Attack and Defense on Point Sets Jiancheng Yang Qiang Zhang Rongyao Fang Bingbing Ni Jinxian Liu Qi Tian 3DPC 112 125 0 28 Feb 2019
The Best Defense Is a Good Offense: Adversarial Attacks to Avoid Modulation Detection Muhammad Zaid Hameed András Gyorgy Deniz Gunduz AAML 83 73 0 27 Feb 2019
Robust Decision Trees Against Adversarial Examples Hongge Chen Huan Zhang Duane S. Boning Cho-Jui Hsieh AAML 142 117 0 27 Feb 2019
Towards Efficient Data Valuation Based on the Shapley Value R. Jia David Dao Wei Ping F. Hubis Nicholas Hynes Nezihe Merve Gürel Yue Liu Ce Zhang Basel Alomair C. Spanos TDI 118 426 0 27 Feb 2019
Grammar Based Directed Testing of Machine Learning Systems Sakshi Udeshi Sudipta Chattopadhyay 83 15 0 26 Feb 2019
Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification Jianlin Li Pengfei Yang Jiangchao Liu Liqian Chen Xiaowei Huang Lijun Zhang AAML 78 80 0 26 Feb 2019
Verification of Non-Linear Specifications for Neural Networks Chongli Qin Krishnamurthy Dvijotham Dvijotham Brendan O'Donoghue Rudy Bunel Robert Stanforth Sven Gowal J. Uesato G. Swirszcz Pushmeet Kohli AAML 73 44 0 25 Feb 2019
Adversarial attacks hidden in plain sight Jan Philip Göpfert André Artelt H. Wersing Barbara Hammer AAML 46 17 0 25 Feb 2019
Batch Virtual Adversarial Training for Graph Convolutional Networks Zhijie Deng Yinpeng Dong Jun Zhu GNN 99 64 0 25 Feb 2019
Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence Yi Han David Hubczenko Paul Montague O. Vel Tamas Abraham Benjamin I. P. Rubinstein C. Leckie T. Alpcan S. Erfani AAML 70 6 0 25 Feb 2019
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks Hadi Salman Greg Yang Huan Zhang Cho-Jui Hsieh Pengchuan Zhang AAML 176 271 0 23 Feb 2019
Adversarial Neural Network Inversion via Auxiliary Knowledge Alignment Ziqi Yang E. Chang Zhenkai Liang MLAU 94 60 0 22 Feb 2019
On the Sensitivity of Adversarial Robustness to Input Data Distributions G. Ding Kry Yik-Chau Lui Xiaomeng Jin Luyu Wang Ruitong Huang OOD 64 60 0 22 Feb 2019
Quantifying Perceptual Distortion of Adversarial Examples Matt Jordan N. Manoj Surbhi Goel A. Dimakis 68 39 0 21 Feb 2019
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations Eric Wong Frank R. Schmidt J. Zico Kolter AAML 97 211 0 21 Feb 2019
advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch G. Ding Luyu Wang Xiaomeng Jin 79 183 0 20 Feb 2019
There are No Bit Parts for Sign Bits in Black-Box Attacks Abdullah Al-Dujaili Una-May O’Reilly AAML 116 20 0 19 Feb 2019
On Evaluating Adversarial Robustness Nicholas Carlini Anish Athalye Nicolas Papernot Wieland Brendel Jonas Rauber Dimitris Tsipras Ian Goodfellow Aleksander Madry Alexey Kurakin ELM AAML 167 906 0 18 Feb 2019
Mockingbird: Defending Against Deep-Learning-Based Website Fingerprinting Attacks with Adversarial Traces Mohammad Saidur Rahman Mohsen Imani Nate Mathews M. Wright AAML 86 81 0 18 Feb 2019
Mitigation of Adversarial Examples in RF Deep Classifiers Utilizing AutoEncoder Pre-training S. Kokalj-Filipovic Rob Miller Nicholas Chang Chi Leung Lau AAML 54 41 0 16 Feb 2019
Adversarial Examples in RF Deep Learning: Detection of the Attack and its Physical Robustness S. Kokalj-Filipovic Rob Miller AAML 60 31 0 16 Feb 2019
DeepFault: Fault Localization for Deep Neural Networks Hasan Ferit Eniser Simos Gerasimou A. Sen AAML 81 88 0 15 Feb 2019
Can Intelligent Hyperparameter Selection Improve Resistance to Adversarial Examples? Cody Burkard Brent Lagesse AAML SILM 36 1 0 14 Feb 2019
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples Kevin Roth Yannic Kilcher Thomas Hofmann AAML 80 176 0 13 Feb 2019
Examining Adversarial Learning against Graph-based IoT Malware Detection Systems Ahmed A. Abusnaina Aminollah Khormali Hisham Alasmary Jeman Park Afsah Anwar Ulku Meteriz Aziz Mohaisen AAML 45 5 0 12 Feb 2019