Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial Attacks
Authors: Thomas Brunner, Frederik Diehl, Michael Truong Le, Alois Knoll | Published: 2018-12-24 | Updated: 2019-05-05
敵対的サンプルの検知
Perturbation Analysis of Learning Algorithms: A Unifying Perspective on Generation of Adversarial Examples
Authors: Emilio Rafael Balda, Arash Behboodi, Rudolf Mathar | Published: 2018-12-15
Thwarting Adversarial Examples: An $L_0$-RobustSparse Fourier Transform
Authors: Mitali Bafna, Jack Murtagh, Nikhil Vyas | Published: 2018-12-12
Adversarial Framing for Image and Video Classification
Authors: Konrad Zolna, Michal Zajac, Negar Rostamzadeh, Pedro O. Pinheiro | Published: 2018-12-11 | Updated: 2019-10-17
Combatting Adversarial Attacks through Denoising and Dimensionality Reduction: A Cascaded Autoencoder Approach
Authors: Rajeev Sahay, Rehana Mahfuz, Aly El Gamal | Published: 2018-12-07
A note on hyperparameters in black-box adversarial examples
Authors: Jamie Hayes | Published: 2018-11-15
Law and Adversarial Machine Learning
Authors: Ram Shankar Siva Kumar, David R. O'Brien, Kendra Albert, Salome Vilojen | Published: 2018-10-25 | Updated: 2018-12-05
One Bit Matters: Understanding Adversarial Examples as the Abuse of Redundancy
Authors: Jingkang Wang, Ruoxi Jia, Gerald Friedland, Bo Li, Costas Spanos | Published: 2018-10-23
A Training-based Identification Approach to VIN Adversarial Examples
Authors: Yingdi Wang, Wenjia Niu, Tong Chen, Yingxiao Xiang, Jingjing Liu, Gang Li, Jiqiang Liu | Published: 2018-10-18
DeepImageSpam: Deep Learning based Image Spam Detection
Authors: Amara Dinesh Kumar, Vinayakumar R, Soman KP | Published: 2018-10-03