Adversarial Security Attacks and Perturbations on Machine Learning and Deep Learning Methods
Authors: Arif Siddiqi | Published: 2019-07-17
敵対的攻撃手法
Latent Adversarial Defence with Boundary-guided Generation
Authors: Xiaowei Zhou, Ivor W. Tsang, Jie Yin | Published: 2019-07-16
Adversarial Sensor Attack on LiDAR-based Perception in Autonomous Driving
Authors: Yulong Cao, Chaowei Xiao, Benjamin Cyr, Yimeng Zhou, Won Park, Sara Rampazzi, Qi Alfred Chen, Kevin Fu, Z. Morley Mao | Published: 2019-07-16 | Updated: 2019-08-20
Bypassing Backdoor Detection Algorithms in Deep Learning
Authors: Te Juin Lester Tan, Reza Shokri | Published: 2019-05-31 | Updated: 2020-06-06
Identifying Classes Susceptible to Adversarial Attacks
Authors: Rangeet Pan, Md Johirul Islam, Shibbir Ahmed, Hridesh Rajan | Published: 2019-05-30
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