Thwarting finite difference adversarial attacks with output randomization
Authors: Haidar Khan, Daniel Park, Azer Khan, Bülent Yener | Published: 2019-05-23
Adversarially Robust Distillation
Authors: Micah Goldblum, Liam Fowl, Soheil Feizi, Tom Goldstein | Published: 2019-05-23 | Updated: 2019-12-02
A Direct Approach to Robust Deep Learning Using Adversarial Networks
Authors: Huaxia Wang, Chun-Nam Yu | Published: 2019-05-23
Deep Reinforcement Learning for Detecting Malicious Websites
Authors: Moitrayee Chatterjee, Akbar Siami Namin | Published: 2019-05-22
A framework for the extraction of Deep Neural Networks by leveraging public data
Authors: Soham Pal, Yash Gupta, Aditya Shukla, Aditya Kanade, Shirish Shevade, Vinod Ganapathy | Published: 2019-05-22
Learning to Confuse: Generating Training Time Adversarial Data with Auto-Encoder
Authors: Ji Feng, Qi-Zhi Cai, Zhi-Hua Zhou | Published: 2019-05-22
DoPa: A Comprehensive CNN Detection Methodology against Physical Adversarial Attacks
Authors: Zirui Xu, Fuxun Yu, Xiang Chen | Published: 2019-05-21 | Updated: 2019-08-28
Few-Shot Adversarial Learning of Realistic Neural Talking Head Models
Authors: Egor Zakharov, Aliaksandra Shysheya, Egor Burkov, Victor Lempitsky | Published: 2019-05-20 | Updated: 2019-09-25
Phish-IRIS: A New Approach for Vision Based Brand Prediction of Phishing Web Pages via Compact Visual Descriptors
Authors: Firat Coskun Dalgic, Ahmet Selman Bozkir, Murat Aydos | Published: 2019-05-19
Taking Care of The Discretization Problem: A Comprehensive Study of the Discretization Problem and A Black-Box Adversarial Attack in Discrete Integer Domain
Authors: Lei Bu, Yuchao Duan, Fu Song, Zhe Zhao | Published: 2019-05-19 | Updated: 2020-04-26