The Space of Transferable Adversarial Examples

11 April 2017

Dan Boneh

Papers citing "The Space of Transferable Adversarial Examples"

31 / 81 papers shown

Title
Analysis of Random Perturbations for Robust Convolutional Neural Networks Adam Dziedzic S. Krishnan OOD AAML 13 1 0 08 Feb 2020
Minimax Defense against Gradient-based Adversarial Attacks Blerta Lindqvist R. Izmailov AAML 6 0 0 04 Feb 2020
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples Nils Lukas Yuxuan Zhang Florian Kerschbaum MLAU FedML AAML 28 144 0 02 Dec 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 13 103 0 13 Nov 2019
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey Olakunle Ibitoye Rana Abou-Khamis Mohamed el Shehaby Ashraf Matrawy M. O. Shafiq AAML 24 68 0 06 Nov 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 21 230 0 24 Jul 2019
Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang Tianyun Zhang Sijia Liu Pin-Yu Chen Jiacen Xu M. Fardad B. Li AAML 23 35 0 09 Jun 2019
Characterizing Bias in Classifiers using Generative Models Daniel J. McDuff Shuang Ma Yale Song Ashish Kapoor 23 47 0 30 May 2019
Cross-Domain Transferability of Adversarial Perturbations Muzammal Naseer Salman H. Khan M. H. Khan F. Khan Fatih Porikli AAML 25 9 0 28 May 2019
Curls & Whey: Boosting Black-Box Adversarial Attacks Yucheng Shi Siyu Wang Yahong Han AAML 13 116 0 02 Apr 2019
Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks Aamir Mustafa Salman Khan Munawar Hayat Roland Göcke Jianbing Shen Ling Shao AAML 9 151 0 01 Apr 2019
On the Vulnerability of CNN Classifiers in EEG-Based BCIs Xiao Zhang Dongrui Wu AAML 8 81 0 31 Mar 2019
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples Kevin Roth Yannic Kilcher Thomas Hofmann AAML 13 175 0 13 Feb 2019
A New Family of Neural Networks Provably Resistant to Adversarial Attacks Rakshit Agrawal Luca de Alfaro D. Helmbold AAML OOD 17 2 0 01 Feb 2019
A Multiversion Programming Inspired Approach to Detecting Audio Adversarial Examples Qiang Zeng Jianhai Su Chenglong Fu Golam Kayas Lannan Luo AAML 11 46 0 26 Dec 2018
Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel Attacks Sanghyun Hong Michael Davinroy Yigitcan Kaya S. Locke Ian Rackow Kevin Kulda Dana Dachman-Soled Tudor Dumitras MIACV 23 90 0 08 Oct 2018
Humans can decipher adversarial images Zhenglong Zhou C. Firestone AAML 9 121 0 11 Sep 2018
On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions Yusuke Tsuzuku Issei Sato AAML 14 62 0 11 Sep 2018
Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks Ambra Demontis Marco Melis Maura Pintor Matthew Jagielski Battista Biggio Alina Oprea Cristina Nita-Rotaru Fabio Roli SILM AAML 11 11 0 08 Sep 2018
Generalization Error in Deep Learning Daniel Jakubovitz Raja Giryes M. Rodrigues AI4CE 16 109 0 03 Aug 2018
Adversarial Examples in Deep Learning: Characterization and Divergence Wenqi Wei Ling Liu Margaret Loper Stacey Truex Lei Yu Mehmet Emre Gursoy Yanzhao Wu AAML SILM 26 18 0 29 Jun 2018
Adversarial Attacks on Neural Networks for Graph Data Daniel Zügner Amir Akbarnejad Stephan Günnemann GNN AAML OOD 18 1,053 0 21 May 2018
Protecting JPEG Images Against Adversarial Attacks Aaditya (Adi) Prakash N. Moran Solomon Garber Antonella DiLillo J. Storer AAML 13 34 0 02 Mar 2018
Understanding and Enhancing the Transferability of Adversarial Examples Lei Wu Zhanxing Zhu Cheng Tai E. Weinan AAML SILM 22 96 0 27 Feb 2018
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality Xingjun Ma Bo-wen Li Yisen Wang S. Erfani S. Wijewickrema Grant Schoenebeck D. Song Michael E. Houle James Bailey AAML 24 726 0 08 Jan 2018
The Robust Manifold Defense: Adversarial Training using Generative Models A. Jalal Andrew Ilyas C. Daskalakis A. Dimakis AAML 23 174 0 26 Dec 2017
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients A. Ross Finale Doshi-Velez AAML 26 675 0 26 Nov 2017
Attacking Binarized Neural Networks A. Galloway Graham W. Taylor M. Moussa MQ AAML 14 104 0 01 Nov 2017
Towards Deep Learning Models Resistant to Adversarial Attacks A. Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 48 11,825 0 19 Jun 2017
Extending Defensive Distillation Nicolas Papernot Patrick D. McDaniel AAML 19 118 0 15 May 2017
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 281 5,833 0 08 Jul 2016