Identifying Classes Susceptible to Adversarial Attacks
Authors: Rangeet Pan, Md Johirul Islam, Shibbir Ahmed, Hridesh Rajan | Published: 2019-05-30
敵対的攻撃手法
Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward
Authors: Adnan Qayyum, Muhammad Usama, Junaid Qadir, Ala Al-Fuqaha | Published: 2019-05-29
Fooling Detection Alone is Not Enough: First Adversarial Attack against Multiple Object Tracking
Authors: Yunhan Jia, Yantao Lu, Junjie Shen, Qi Alfred Chen, Zhenyu Zhong, Tao Wei | Published: 2019-05-27 | Updated: 2019-05-30
Weight Map Layer for Noise and Adversarial Attack Robustness
Authors: Mohammed Amer, Tomás Maul | Published: 2019-05-02 | Updated: 2020-12-02
NATTACK: Learning the Distributions of Adversarial Examples for an Improved Black-Box Attack on Deep Neural Networks
Authors: Yandong Li, Lijun Li, Liqiang Wang, Tong Zhang, Boqing Gong | Published: 2019-05-01 | Updated: 2019-12-09
Detecting Adversarial Examples through Nonlinear Dimensionality Reduction
Authors: Francesco Crecchi, Davide Bacciu, Battista Biggio | Published: 2019-04-30 | Updated: 2019-05-01
Adversarial Training and Robustness for Multiple Perturbations
Authors: Florian Tramèr, Dan Boneh | Published: 2019-04-30 | Updated: 2019-10-18
A Robust Approach for Securing Audio Classification Against Adversarial Attacks
Authors: Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich | Published: 2019-04-24 | Updated: 2019-11-25
A Target-Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer Learning
Authors: Shahbaz Rezaei, Xin Liu | Published: 2019-04-08 | Updated: 2020-01-29
Practical Hidden Voice Attacks against Speech and Speaker Recognition Systems
Authors: Hadi Abdullah, Washington Garcia, Christian Peeters, Patrick Traynor, Kevin R. B. Butler, Joseph Wilson | Published: 2019-03-18