Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing
Authors: Jingyi Wang, Jun Sun, Peixin Zhang, Xinyu Wang | Published: 2018-05-14 | Updated: 2018-05-17
モデルの頑健性保証
How Robust are Deep Neural Networks?
Authors: Biswa Sengupta, Karl J. Friston | Published: 2018-04-30
Query-Efficient Black-Box Attack Against Sequence-Based Malware Classifiers
Authors: Ishai Rosenberg, Asaf Shabtai, Yuval Elovici, Lior Rokach | Published: 2018-04-23 | Updated: 2020-10-03
ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector
Authors: Shang-Tse Chen, Cory Cornelius, Jason Martin, Duen Horng Chau | Published: 2018-04-16 | Updated: 2019-05-01
On the Robustness of the CVPR 2018 White-Box Adversarial Example Defenses
Authors: Anish Athalye, Nicholas Carlini | Published: 2018-04-10
Adversarial Training Versus Weight Decay
Authors: Angus Galloway, Thomas Tanay, Graham W. Taylor | Published: 2018-04-10 | Updated: 2018-07-23
Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations
Authors: Alex Lamb, Jonathan Binas, Anirudh Goyal, Dmitriy Serdyuk, Sandeep Subramanian, Ioannis Mitliagkas, Yoshua Bengio | Published: 2018-04-07
Adversarial Attacks and Defences Competition
Authors: Alexey Kurakin, Ian Goodfellow, Samy Bengio, Yinpeng Dong, Fangzhou Liao, Ming Liang, Tianyu Pang, Jun Zhu, Xiaolin Hu, Cihang Xie, Jianyu Wang, Zhishuai Zhang, Zhou Ren, Alan Yuille, Sangxia Huang, Yao Zhao, Yuzhe Zhao, Zhonglin Han, Junjiajia Long, Yerkebulan Berdibekov, Takuya Akiba, Seiya Tokui, Motoki Abe | Published: 2018-03-31
Defending against Adversarial Images using Basis Functions Transformations
Authors: Uri Shaham, James Garritano, Yutaro Yamada, Ethan Weinberger, Alex Cloninger, Xiuyuan Cheng, Kelly Stanton, Yuval Kluger | Published: 2018-03-28 | Updated: 2018-04-16
Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization
Authors: Daniel Jakubovitz, Raja Giryes | Published: 2018-03-23 | Updated: 2019-05-28