Copy and Paste: A Simple But Effective Initialization Method for Black-Box Adversarial Attacks
Authors: Thomas Brunner, Frederik Diehl, Alois Knoll | Published: 2019-06-14 | Updated: 2019-12-29
Adversarial Perturbation Techniques
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
Authors: Yuzhe Yang, Guo Zhang, Dina Katabi, Zhi Xu | Published: 2019-05-28
Snooping Attacks on Deep Reinforcement Learning
Authors: Matthew Inkawhich, Yiran Chen, Hai Li | Published: 2019-05-28 | Updated: 2020-01-15
Semantics Preserving Adversarial Learning
Authors: Ousmane Amadou Dia, Elnaz Barshan, Reza Babanezhad | Published: 2019-03-10 | Updated: 2019-12-21
Adversarial Examples on Graph Data: Deep Insights into Attack and Defense
Authors: Huijun Wu, Chen Wang, Yuriy Tyshetskiy, Andrew Docherty, Kai Lu, Liming Zhu | Published: 2019-03-05 | Updated: 2019-05-22
PuVAE: A Variational Autoencoder to Purify Adversarial Examples
Authors: Uiwon Hwang, Jaewoo Park, Hyemi Jang, Sungroh Yoon, Nam Ik Cho | Published: 2019-03-02
Evaluating Adversarial Evasion Attacks in the Context of Wireless Communications
Authors: Bryse Flowers, R. Michael Buehrer, William C. Headley | Published: 2019-03-01
CapsAttacks: Robust and Imperceptible Adversarial Attacks on Capsule Networks
Authors: Alberto Marchisio, Giorgio Nanfa, Faiq Khalid, Muhammad Abdullah Hanif, Maurizio Martina, Muhammad Shafique | Published: 2019-01-28 | Updated: 2019-05-24
On the Limitation of Local Intrinsic Dimensionality for Characterizing the Subspaces of Adversarial Examples
Authors: Pei-Hsuan Lu, Pin-Yu Chen, Chia-Mu Yu | Published: 2018-03-26
Clipping free attacks against artificial neural networks
Authors: Boussad Addad, Jerome Kodjabachian, Christophe Meyer | Published: 2018-03-26 | Updated: 2018-03-28