Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
Authors: Xuanqing Liu, Yao Li, Chongruo Wu, Cho-Jui Hsieh | Published: 2018-10-01 | Updated: 2019-05-04
モデルの頑健性保証
Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks
Authors: Kenneth T. Co, Luis Muñoz-González, Sixte de Maupeou, Emil C. Lupu | Published: 2018-09-30 | Updated: 2019-11-23
Adversarial Attacks on Cognitive Self-Organizing Networks: The Challenge and the Way Forward
Authors: Muhammad Usama, Junaid Qadir, Ala Al-Fuqaha | Published: 2018-09-26
Neural Networks with Structural Resistance to Adversarial Attacks
Authors: Luca de Alfaro | Published: 2018-09-25
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
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