Towards Backdoor Attacks and Defense in Robust Machine Learning Models
Authors: Ezekiel Soremekun, Sakshi Udeshi, Sudipta Chattopadhyay | Published: 2020-02-25 | Updated: 2023-01-11
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Adversarial Perturbations Prevail in the Y-Channel of the YCbCr Color Space
Authors: Camilo Pestana, Naveed Akhtar, Wei Liu, David Glance, Ajmal Mian | Published: 2020-02-25
HYDRA: Pruning Adversarially Robust Neural Networks
Authors: Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana | Published: 2020-02-24 | Updated: 2020-11-10
Approximate Data Deletion from Machine Learning Models
Authors: Zachary Izzo, Mary Anne Smart, Kamalika Chaudhuri, James Zou | Published: 2020-02-24 | Updated: 2021-02-23
Stealing Black-Box Functionality Using The Deep Neural Tree Architecture
Authors: Daniel Teitelman, Itay Naeh, Shie Mannor | Published: 2020-02-23
An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning
Authors: Xue Yang, Yan Feng, Weijun Fang, Jun Shao, Xiaohu Tang, Shu-Tao Xia, Rongxing Lu | Published: 2020-02-23 | Updated: 2021-08-15
Neuron Shapley: Discovering the Responsible Neurons
Authors: Amirata Ghorbani, James Zou | Published: 2020-02-23 | Updated: 2020-11-13
Non-Intrusive Detection of Adversarial Deep Learning Attacks via Observer Networks
Authors: Kirthi Shankar Sivamani, Rajeev Sahay, Aly El Gamal | Published: 2020-02-22
Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers
Authors: Chen Zhu, Renkun Ni, Ping-yeh Chiang, Hengduo Li, Furong Huang, Tom Goldstein | Published: 2020-02-22
Using Single-Step Adversarial Training to Defend Iterative Adversarial Examples
Authors: Guanxiong Liu, Issa Khalil, Abdallah Khreishah | Published: 2020-02-22 | Updated: 2020-02-27