Adversarial Examples: Opportunities and Challenges
Authors: Jiliang Zhang, Chen Li | Published: 2018-09-13 | Updated: 2019-09-23
モデルの頑健性保証
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
Adversarial Attacks on Node Embeddings via Graph Poisoning
Authors: Aleksandar Bojchevski, Stephan Günnemann | Published: 2018-09-04 | Updated: 2019-05-27
Lipschitz regularized Deep Neural Networks generalize and are adversarially robust
Authors: Chris Finlay, Jeff Calder, Bilal Abbasi, Adam Oberman | Published: 2018-08-28 | Updated: 2019-09-12
Mitigation of Adversarial Attacks through Embedded Feature Selection
Authors: Ziyi Bao, Luis Muñoz-González, Emil C. Lupu | Published: 2018-08-16