Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable Bytes
Authors: Keane Lucas, Mahmood Sharif, Lujo Bauer, Michael K. Reiter, Saurabh Shintre | Published: 2019-12-19 | Updated: 2021-10-25
敵対的サンプル
Stealing Knowledge from Protected Deep Neural Networks Using Composite Unlabeled Data
Authors: Itay Mosafi, Eli David, Nathan S. Netanyahu | Published: 2019-12-09
Hardening Random Forest Cyber Detectors Against Adversarial Attacks
Authors: Giovanni Apruzzese, Mauro Andreolini, Michele Colajanni, Mirco Marchetti | Published: 2019-12-09
Principal Component Properties of Adversarial Samples
Authors: Malhar Jere, Sandro Herbig, Christine Lind, Farinaz Koushanfar | Published: 2019-12-07
Label-Consistent Backdoor Attacks
Authors: Alexander Turner, Dimitris Tsipras, Aleksander Madry | Published: 2019-12-05 | Updated: 2019-12-06
A Method for Computing Class-wise Universal Adversarial Perturbations
Authors: Tejus Gupta, Abhishek Sinha, Nupur Kumari, Mayank Singh, Balaji Krishnamurthy | Published: 2019-12-01
Computer Systems Have 99 Problems, Let’s Not Make Machine Learning Another One
Authors: David Mohaisen, Songqing Chen | Published: 2019-11-28
An Adaptive View of Adversarial Robustness from Test-time Smoothing Defense
Authors: Chao Tang, Yifei Fan, Anthony Yezzi | Published: 2019-11-26
Playing it Safe: Adversarial Robustness with an Abstain Option
Authors: Cassidy Laidlaw, Soheil Feizi | Published: 2019-11-25
One Man’s Trash is Another Man’s Treasure: Resisting Adversarial Examples by Adversarial Examples
Authors: Chang Xiao, Changxi Zheng | Published: 2019-11-25 | Updated: 2019-11-27