Adversarial Defense via Data Dependent Activation Function and Total Variation Minimization
Authors: Bao Wang, Alex T. Lin, Wei Zhu, Penghang Yin, Andrea L. Bertozzi, Stanley J. Osher | Published: 2018-09-23 | Updated: 2020-04-29
モデルの頑健性保証
Defensive Dropout for Hardening Deep Neural Networks under Adversarial Attacks
Authors: Siyue Wang, Xiao Wang, Pu Zhao, Wujie Wen, David Kaeli, Peter Chin, Xue Lin | Published: 2018-09-13
Query-Efficient Black-Box Attack by Active Learning
Authors: Pengcheng Li, Jinfeng Yi, Lijun Zhang | Published: 2018-09-13
Adversarial Examples: Opportunities and Challenges
Authors: Jiliang Zhang, Chen Li | Published: 2018-09-13 | Updated: 2019-09-23
Deep Learning in Information Security
Authors: Stefan Thaler, Vlado Menkovski, Milan Petkovic | Published: 2018-09-12
The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure
Authors: Saeed Mahloujifar, Dimitrios I. Diochnos, Mohammad Mahmoody | Published: 2018-09-09 | Updated: 2018-11-06
Structure-Preserving Transformation: Generating Diverse and Transferable Adversarial Examples
Authors: Dan Peng, Zizhan Zheng, Xiaofeng Zhang | Published: 2018-09-08 | Updated: 2018-12-22
Detecting Potential Local Adversarial Examples for Human-Interpretable Defense
Authors: Xavier Renard, Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Marcin Detyniecki | Published: 2018-09-07
Adversarial Reprogramming of Text Classification Neural Networks
Authors: Paarth Neekhara, Shehzeen Hussain, Shlomo Dubnov, Farinaz Koushanfar | Published: 2018-09-06 | Updated: 2019-08-15
Bridging machine learning and cryptography in defence against adversarial attacks
Authors: Olga Taran, Shideh Rezaeifar, Slava Voloshynovskiy | Published: 2018-09-05