Detecting Adversarial Examples – A Lesson from Multimedia Forensics
Authors: Pascal Schöttle, Alexander Schlögl, Cecilia Pasquini, Rainer Böhme | Published: 2018-03-09
敵対的攻撃手法
Adversarial Perturbation Intensity Achieving Chosen Intra-Technique Transferability Level for Logistic Regression
Authors: Martin Gubri | Published: 2018-01-06
Did you hear that? Adversarial Examples Against Automatic Speech Recognition
Authors: Moustafa Alzantot, Bharathan Balaji, Mani Srivastava | Published: 2018-01-02
Building Robust Deep Neural Networks for Road Sign Detection
Authors: Arkar Min Aung, Yousef Fadila, Radian Gondokaryono, Luis Gonzalez | Published: 2017-12-26
Query-limited Black-box Attacks to Classifiers
Authors: Fnu Suya, Yuan Tian, David Evans, Paolo Papotti | Published: 2017-12-23
Query-Efficient Black-box Adversarial Examples (superceded)
Authors: Andrew Ilyas, Logan Engstrom, Anish Athalye, Jessy Lin | Published: 2017-12-19 | Updated: 2018-04-06
When Not to Classify: Anomaly Detection of Attacks (ADA) on DNN Classifiers at Test Time
Authors: David J. Miller, Yulia Wang, George Kesidis | Published: 2017-12-18 | Updated: 2018-06-28
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models
Authors: Wieland Brendel, Jonas Rauber, Matthias Bethge | Published: 2017-12-12 | Updated: 2018-02-16
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning
Authors: Battista Biggio, Fabio Roli | Published: 2017-12-08 | Updated: 2018-07-19
Generative Adversarial Perturbations
Authors: Omid Poursaeed, Isay Katsman, Bicheng Gao, Serge Belongie | Published: 2017-12-06 | Updated: 2018-07-06