Suspicion-Free Adversarial Attacks on Clustering Algorithms
Authors: Anshuman Chhabra, Abhishek Roy, Prasant Mohapatra | Published: 2019-11-16
敵対的攻撃手法
DomainGAN: Generating Adversarial Examples to Attack Domain Generation Algorithm Classifiers
Authors: Isaac Corley, Jonathan Lwowski, Justin Hoffman | Published: 2019-11-14 | Updated: 2020-02-14
There is Limited Correlation between Coverage and Robustness for Deep Neural Networks
Authors: Yizhen Dong, Peixin Zhang, Jingyi Wang, Shuang Liu, Jun Sun, Jianye Hao, Xinyu Wang, Li Wang, Jin Song Dong, Dai Ting | Published: 2019-11-14
Adversarial Examples in Modern Machine Learning: A Review
Authors: Rey Reza Wiyatno, Anqi Xu, Ousmane Dia, Archy de Berker | Published: 2019-11-13 | Updated: 2019-11-15
On Robustness to Adversarial Examples and Polynomial Optimization
Authors: Pranjal Awasthi, Abhratanu Dutta, Aravindan Vijayaraghavan | Published: 2019-11-12
Patch augmentation: Towards efficient decision boundaries for neural networks
Authors: Marcus D. Bloice, Peter M. Roth, Andreas Holzinger | Published: 2019-11-08 | Updated: 2019-11-25
White-Box Target Attack for EEG-Based BCI Regression Problems
Authors: Lubin Meng, Chin-Teng Lin, Tzyy-Ring Jung, Dongrui Wu | Published: 2019-11-07
Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks
Authors: David Stutz, Matthias Hein, Bernt Schiele | Published: 2019-10-14 | Updated: 2020-06-30
Hear “No Evil”, See “Kenansville”: Efficient and Transferable Black-Box Attacks on Speech Recognition and Voice Identification Systems
Authors: Hadi Abdullah, Muhammad Sajidur Rahman, Washington Garcia, Logan Blue, Kevin Warren, Anurag Swarnim Yadav, Tom Shrimpton, Patrick Traynor | Published: 2019-10-11
Adversarial Training: embedding adversarial perturbations into the parameter space of a neural network to build a robust system
Authors: Shixian Wen, Laurent Itti | Published: 2019-10-09