Sparse and Imperceivable Adversarial Attacks
Authors: Francesco Croce, Matthias Hein | Published: 2019-09-11
Attack Method
PDA: Progressive Data Augmentation for General Robustness of Deep Neural Networks
Authors: Hang Yu, Aishan Liu, Xianglong Liu, Gengchao Li, Ping Luo, Ran Cheng, Jichen Yang, Chongzhi Zhang | Published: 2019-09-11 | Updated: 2020-02-24
Effectiveness of Adversarial Examples and Defenses for Malware Classification
Authors: Robert Podschwadt, Hassan Takabi | Published: 2019-09-10
Poisoning Attacks with Generative Adversarial Nets
Authors: Luis Muñoz-González, Bjarne Pfitzner, Matteo Russo, Javier Carnerero-Cano, Emil C. Lupu | Published: 2019-06-18 | Updated: 2019-09-25
On the Robustness of the Backdoor-based Watermarking in Deep Neural Networks
Authors: Masoumeh Shafieinejad, Jiaqi Wang, Nils Lukas, Xinda Li, Florian Kerschbaum | Published: 2019-06-18 | Updated: 2019-11-26
Membership Privacy for Machine Learning Models Through Knowledge Transfer
Authors: Virat Shejwalkar, Amir Houmansadr | Published: 2019-06-15 | Updated: 2020-12-31
Combatting Adversarial Attacks through Denoising and Dimensionality Reduction: A Cascaded Autoencoder Approach
Authors: Rajeev Sahay, Rehana Mahfuz, Aly El Gamal | Published: 2018-12-07
Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks
Authors: Kang Liu, Brendan Dolan-Gavitt, Siddharth Garg | Published: 2018-05-30
What we learn from learning – Understanding capabilities and limitations of machine learning in botnet attacks
Authors: David Santana, Shan Suthaharan, Somya Mohanty | Published: 2018-05-03
MEADE: Towards a Malicious Email Attachment Detection Engine
Authors: Ethan M. Rudd, Richard Harang, Joshua Saxe | Published: 2018-04-22